JP2013102851A - Medical imaging system, medical image processing apparatus, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To make a radiographing technician enable to immediately recognize the defective image in which the reference provided beforehand as a medical image for the diagnosis is not filled, and to aim at the prevention of missing the defective image and the reduction of the patient's burden.SOLUTION: In a medical imaging system 100, FPD9 generates a medical image that is a still image and a preview image in which the medical image is reduced by taking an image of the specific part of a human body as a subject, and transmits them to a console 5 for photographing. A controller 51 of the console 5 for photographing determines whether the photographed medical image meets the reference provided beforehand as a medical image for diagnosis, or not by analyzing the preview image, and when determined not to meet the reference provided beforehand as a medical image for diagnosis, the warning is displayed on a display 54.

Description

  The present invention relates to a medical image photographing system, a medical image processing apparatus, and a program.

  2. Description of the Related Art Conventionally, there is known a medical image photographing system that performs radiography on a specific part that is a diagnosis target of a human body and generates a digital medical image as a still image.

  In radiography, medical images obtained by radiography include, for example, images in which the subject is improperly positioned and a specific part is missing, images in which the subject is moving, images in which the radiation dose is insufficient, etc. If the image does not satisfy the criteria as a diagnostic medical image (a defective image inappropriate for diagnosis), re-imaging is required. And it is preferable to be able to determine whether re-photographing is necessary or not early.

  Therefore, for example, in Patent Document 1, a reduced image of a medical image captured by an FPD (Flat Panel Detector) is transferred to a console in advance of the medical image, and the reduced image is displayed at an early stage as a preview image on the console. A radiographic image generation system is described in which it is possible to quickly check whether a captured medical image is a defective image that requires re-imaging in which positioning errors or body movements have occurred. .

In addition, a system that warns an image inappropriate for diagnosis by analyzing a medical image obtained by radiography has been proposed.
For example, in Patent Document 2, the presence or absence of body movement of a subject at the time of photographing in a medical image of a still image is determined, and a warning is given based on the determination result, and at the same time an enlarged display is performed, thereby overlooking the body movement image. A medical imaging system to prevent is described.
Patent Document 3 describes a radiation image reading system that determines the quality of positioning of image data obtained by imaging and issues a warning based on the determination result.

JP 2010-214057 A Japanese Patent No. 4539186 Japanese Patent Laid-Open No. 4-364834

  In the system described in Patent Document 1, since a preview image can be checked immediately after shooting, the image is checked as it is without releasing the positioning after shooting, and if the image is unsuitable for diagnosis, the positioning is finely adjusted. It is possible to perform re-photographing only. However, severely ill patients suffer from just maintaining the positioning during imaging, and it is desired to judge the quality of medical images as soon as possible after imaging and release them from the positioning state.

  Moreover, since it is difficult for critically ill patients to move to the imaging room, imaging is performed at the bedside by a round-trip car. In this case, the medical image is checked on a portable console, but the screen is small for ease of carrying, so it is difficult to check the image compared to a stationary console. Since it is inferior to a medical image for diagnosis, an image that needs to be re-photographed due to a positioning error or body movement may be missed. In addition, when the preview image is checked more carefully in order to reduce the risk of missing these, the time required for the check increases, so that the burden on the patient to maintain the positioning is large.

  On the other hand, as disclosed in Patent Documents 2 and 3, when analyzing a medical image for diagnosis and warning an image inappropriate for diagnosis, it takes time until the medical image for diagnosis is acquired and displayed on the console. Cost. Therefore, in order to reduce the positioning burden on the patient, it is necessary to cancel the positioning once and confirm the medical image after imaging. If a medical image defect is noticed by a warning after completion of acquisition of a medical image at the console, it is necessary to perform positioning work again, which is a problem for both the imaging technician and the patient.

  An object of the present invention is to enable a radiographer to immediately recognize a defective image that does not satisfy a predetermined standard as a medical image for diagnosis, thereby preventing oversight of the defective image and reducing the burden on the patient. That is.

In order to solve the above-described problem, a medical image photographing system according to claim 1 is provided.
Image generating means for generating a medical image as a still image by photographing a specific part of the human body as a subject;
Preview image generating means for generating a preview image by reducing the medical image;
Display means for displaying the preview image;
Image determination means for determining whether or not the medical image satisfies a predetermined criterion as a medical image for diagnosis by analyzing the preview image;
Control means for displaying a warning on the display means when the image determination means determines that the medical image does not satisfy a predetermined criterion as a diagnostic medical image;
Is provided.

The invention according to claim 2 is the invention according to claim 1,
The image determination means analyzes the preview image to determine whether the medical image is an image without a defect of the specific part, whether the subject has no body movement, It is determined whether at least one of the images is an image in which the radiation exposure amount exceeds a predetermined reference.

The invention according to claim 3 is the invention according to claim 1,
Image processing means for performing image processing on the preview image;
The image determination unit analyzes the preview image or the preview image image-processed by the image processing unit to determine whether the medical image is an image having no defect in the specific part. At least one of whether the image has no motion, whether the radiation dose at the time of imaging exceeds a predetermined standard, and whether the image processing condition is an appropriate image. Judge one.

The invention according to claim 4
An image processing apparatus connected to an image generation means for generating a medical image that is a still image and a preview image obtained by reducing the medical image by photographing a specific part of a human body as a subject, so that data can be transmitted and received.
Display means for displaying the preview image;
Analyzing the preview image to determine whether the medical image is an image satisfying a predetermined criterion;
Control means for displaying a warning on the display means when the image determination means determines that the medical image does not satisfy a predetermined criterion as a diagnostic medical image;
Is provided.

The program of the invention described in claim 5 is:
A computer used for a medical image processing apparatus connected to be capable of transmitting and receiving data with a medical image that is a still image by capturing a specific part of the human body as a subject and an image generating unit that generates a preview image obtained by reducing the medical image,
Display means for displaying the preview image;
Image determination means for determining whether or not the medical image is an image satisfying a predetermined criterion by analyzing the preview image;
Control means for displaying a warning on the display means when the image determination means determines that the medical image does not satisfy a predetermined criterion as a diagnostic medical image;
To function as.

  According to the present invention, the imaging engineer can immediately recognize a defective image that does not satisfy a predetermined standard as a medical image for diagnosis, so that it is possible to prevent oversight of the defective image and reduce the burden on the patient. Can be planned.

1 is a diagram illustrating an overall configuration of a medical image photographing system according to an embodiment. It is a block diagram which shows the functional structure of the imaging | photography console. It is a flowchart which shows the medical image generation process performed by the control part of the imaging console. It is a flowchart which shows the positioning determination process which is an example of the image determination process performed in step S9 of FIG. It is a figure for demonstrating the partial area | region which touches the boundary line of an irradiation field. It is a figure for demonstrating the small area | region where a feature-value is calculated. It is the graph which plotted the feature-value calculated from the several image (sample image) with which it is known beforehand whether the defect | deletion of the lung field exists in the space centering on each feature-value used for positioning determination. It is a figure which shows typically the creation process of a lower end determination device. It is a figure which shows an example of a positioning warning screen. It is a flowchart which shows the body movement determination process which is an example of the image determination process performed in step S9 of FIG. It is a figure which shows typically the response of the spatial frequency in a still image. It is a figure which shows typically the response of the spatial frequency in the still image (body motion image) with a body motion in a horizontal direction. It is a figure which shows typically the response of the spatial frequency in the image containing the edge of a horizontal direction. It is a figure which shows the relationship between the vertical spatial frequency and the response in the image containing a horizontal edge and the image which does not contain an edge. It is a figure which shows an example of the lung field area | region extracted from the medical image. It is a figure for demonstrating the zone | band which calculates the maximum value or integral value of a response. It is a figure which shows an example of the local area | region which does not contain the edge extracted in step S303 of FIG. It is a figure for demonstrating the zone | band used as the calculation object of the parameter | index of the response of the high spatial frequency component of a vertical direction and a horizontal direction. It is a figure for demonstrating the band used as the calculation object of the parameter | index of the response of the high spatial frequency component of the diagonal direction. It is a figure for demonstrating the calculation method of a body movement feature-value. It is a figure which shows the determination process of the expansion area | region enlargedly displayed on a body movement warning screen (1st step). It is a figure which shows the determination process of the expansion area enlargedly displayed on a body movement warning screen (2nd step). It is a figure which shows the determination process of the expansion area | region enlargedly displayed on a body movement warning screen (3rd step). It is a figure which shows an example of a body movement warning screen. It is a flowchart which shows the dose determination process which is an example of the image determination process performed in step S9 of FIG. It is a figure which shows an example of a dose warning screen. It is a flowchart which shows the image process condition determination process which is an example of the image determination process performed in step S9 of FIG. It is a figure which shows an example of an image process warning screen. It is a figure which shows an example of the medical image imaging system for patients with difficult movement.

  Hereinafter, embodiments of a medical image photographing system according to the present invention will be described with reference to the drawings. However, the present invention is not limited to the following illustrated examples.

(Configuration of medical imaging system)
First, the configuration of the medical image photographing system 100 in the present embodiment will be described.
FIG. 1 is a diagram showing an example of the overall configuration of a medical image photographing system 100 according to an embodiment of the present invention. The medical image photographing system 100 is a system that generates a still image of a subject by irradiating radiation on a specific part of the patient's body (that is, a diagnostic target part (imaging part)). FIG. 1 shows a case where the medical image photographing system 100 is constructed in the photographing room Rm.

  In the photographing room Rm, for example, a bucky device 1 for standing photographing, a bucky device 2 for standing photographing, a radiation source 3, a photographing console 5, an operation console 6, and an access point AP are provided. Is provided. The photographing room Rm is provided with a front room Ra and a photographing room Rb, and the front room Ra is provided with a photographing console 5 and a console 6 to prevent exposure of an operator such as a photographing engineer. Yes.

Hereinafter, each device in the photographing room Rm will be described.
The bucky device 1 is a device for holding the FPD 9 and performing shooting when shooting in a standing position. The bucky device 1 includes a holding portion 12a for holding the FPD 9 and a connector 12b for connecting a connector of the FPD 9 attached to the holding portion 12a. The connector 12b transmits / receives data to / from the FPD 9 attached to the holding unit 12a and supplies power to the FPD 9. The bucky device 1 also has an interface for transmitting / receiving data to / from an external device such as the imaging console 5 via the access point AP via a communication cable, and for moving the holding unit 12a vertically or horizontally. A foot switch is provided.

  The bucky device 2 is a device for holding the FPD 9 when shooting in the supine position. The bucky device 2 includes a holding portion 22a for holding the FPD 9 and a connector 22b for connecting a connector of the FPD 9 attached to the holding portion 22a. The connector 22b transmits / receives data to / from the FPD 9 attached to the holding unit 22a and supplies power to the FPD 9. The bucky device 2 also includes an interface for transmitting / receiving data to / from an external device such as the imaging console 5 via a communication cable via an access point AP, and a subject table 26 for placing a subject.

  The radiation source 3 is suspended from the ceiling of the imaging room Rm, for example, and is activated based on an instruction from the console 6 at the time of imaging, and adjusted to a predetermined position and orientation by a drive mechanism (not shown). It has become. Then, by changing the irradiation direction of radiation, radiation (X-rays) can be irradiated to the FPD 9 mounted on the standing-side bucky device 1 or the lying-down bucky device 2. . Further, the radiation source 3 irradiates the radiation once in accordance with an instruction from the console 6 and takes a still image.

  The imaging console 5 displays the reduced image (preview image) of the medical image transmitted from the FPD 9 by performing correction processing and image processing, or performs correction processing and image processing on the medical image transmitted from the FPD 9 for diagnosis. This is a medical image processing apparatus for generating and displaying medical images for medical use. The imaging console 5 is connected to a HIS / RIS (Hospital Information System / Radiology Information System) 7, a diagnostic console 8, a server device 10, etc. via a LAN (Local Area Network). A list of the transmitted imaging order information is displayed, and the specified imaging order information and medical image are associated with each other and transmitted to the server device 10.

  FIG. 2 shows a configuration example of a main part of the imaging console 5. As shown in FIG. 2, the imaging console 5 includes a control unit 51, a storage unit 52, an input unit 53, a display unit 54, a communication I / F 55, a network communication unit 56, and the like. 57 is connected.

The control unit 51 includes a CPU, a RAM, and the like. The CPU of the control unit 51 reads out various programs such as system programs and processing programs stored in the storage unit 52, expands them in the RAM, and executes various processes according to the expanded programs.
For example, the control unit 51 makes an inquiry to the HIS / RIS 7 via the network communication unit 56 every predetermined time, and acquires the imaging order information newly registered in the HIS / RIS 7.
Further, for example, the control unit 51 implements functions as an image determination unit, an image processing unit, and a control unit by executing the imaging console side processing of the medical image generation processing illustrated in FIG.

The storage unit 52 includes, for example, an HDD (Hard Disk Drive), a semiconductor nonvolatile memory, or the like.
The storage unit 52 stores various programs and data.
For example, in addition to storing various programs in the storage unit 52, image processing parameters for adjusting the image data of medical images to an image quality suitable for diagnosis for each part (tone curve used for tone processing) The defined look-up table, frequency processing enhancement level, etc.) are stored.

The storage unit 52 stores characteristic information of the FPD 9. Here, the characteristic information is a characteristic of the detecting element of the FPD 9 or a scintillator panel.
The storage unit 52 stores imaging order information transmitted from the HIS / RIS 7 every predetermined time.

  The input unit 53 includes a keyboard having character input keys, numeric input keys, various function keys, and the like, and a pointing device such as a mouse, and a key pressing signal pressed by the keyboard and an operation signal by the mouse. Are output to the control unit 51 as an input signal.

The display unit 54 includes, for example, a monitor such as a CRT (Cathode Ray Tube) or an LCD (Liquid Crystal Display), and displays various screens according to instructions of a display signal input from the control unit 51.
A pressure-sensitive (resistive film pressure type) touch panel (not shown) in which transparent electrodes are arranged in a grid pattern is formed on the screen of the display unit 54, and the display unit 54 and the input unit 53 are configured integrally. It may be a touch screen. In this case, the touch panel is configured to detect the XY coordinates of the power point pressed by a finger, a touch pen, or the like as a voltage value, and output the detected position signal to the control unit 51 as an operation signal. The display unit 54 is a general PC (Personal Computer).
It may be of a higher definition than the monitor used for.

  The communication I / F 55 is an interface for connecting to the Bucky device 1, the Bucky device 2, the radiation source 3, and the FPD 9 via the access point AP and performing data transmission / reception wirelessly or by wire. In the present embodiment, the communication I / F 55 transmits a polling signal to the FPD 9 as necessary via the access point AP.

  The network communication unit 56 includes a network interface or the like, and transmits / receives data to / from an external device connected to the communication network N via a switching hub.

  The console 6 is connected to the radiation source 3 in the imaging room and is an input device for inputting a radiation irradiation instruction to the radiation source 3, setting of radiation irradiation conditions, and the like. In the present embodiment, the console 6 has a storage device in which imaging conditions (radiation irradiation conditions and image reading conditions) are stored in association with the imaging region, and the radiation irradiation conditions corresponding to the selected imaging region are set. Set to radiation source 3. The radiation irradiation conditions are, for example, an X-ray tube current value, an X-ray tube voltage value, a filter type, an SID (Source to Image-receptor Distance), and the like.

  The HIS / RIS 7 generates imaging order information in response to a registration operation by an operator based on an inquiry result or the like. The imaging order information includes, for example, patient information such as the patient's name, sex, age, height, weight, etc., information related to imaging reservations such as imaging site, imaging direction, position (standing position, standing position), imaging method, and the like. Yes. Note that the shooting order information is not limited to the information exemplified here, but may include other information, or may be a part of the information exemplified above.

  The diagnosis console 8 is a computer device that acquires medical images from the server device 10 and displays the acquired images to allow a doctor to make an interpretation diagnosis.

The FPD 9 is a radiation detector that includes a control unit, a detection unit, a storage unit, a connector, a battery, a wireless communication unit, and the like.
The detection unit of the FPD 9 includes, for example, a glass substrate, and detects, at a predetermined position on the substrate, radiation that has been irradiated from the radiation source 3 and transmitted through at least the subject according to the intensity thereof. A plurality of detection elements that are converted into electrical signals and accumulated are two-dimensionally arranged. The detection element is configured by a semiconductor image sensor such as a photodiode. Each detection element is connected to a switching unit such as a TFT (Thin Film Transistor), for example, and the switching unit controls the accumulation and reading of electric signals.

The control unit of the FPD 9 controls the switching unit of the detection unit based on the image reading conditions stored in the storage unit, and switches the reading of the electrical signal accumulated in each detection element, and accumulates in the detection unit. Image data of a medical image (still image) is generated by reading the electrical signal. Then, the control unit reduces the generated medical image to generate a preview image, and outputs the generated preview image and image data of the medical image to the imaging console 5 via the connector and the bucky device 1 or 2. . That is, the FPD 9 functions as a medical image generation unit and a preview image generation unit. Each pixel constituting the generated still image indicates a signal value (herein referred to as a density value) output from each detection element of the detection unit.
The connector of the FPD 9 is connected to the connector on the Bucky devices 1 and 2 side, and performs data transmission / reception with the Bucky device 1 or 2. The connector of the FPD 9 supplies power supplied from the connector of the bucky device 1 or 2 to each function unit. Note that the battery may be charged.
The FPD 9 is configured to be battery-driven and wirelessly communicated when used alone without being attached to the Bucky. When the FPD 9 is loaded into the Bucky device 1 or 2, the battery / wireless system is switched from the battery / wireless system to the wired / power supply system by connecting a connector. Can do. Accordingly, even when a plurality of patients are continuously photographed, it is not necessary to worry about running out of the battery.

  The server device 10 includes a database that stores medical image data and interpretation reports transmitted from the imaging console 5 in association with imaging order information. Further, the server device 10 reads a medical image from the database in response to a request from the diagnostic console 8 and transmits the medical image to the diagnostic console 8.

(Shooting operation)
Next, a photographing operation in the medical image photographing system 100 will be described.
FIG. 3 shows a flow of medical image generation processing executed in the medical image photographing system 100.

  First, an operator such as a shooting engineer operates the input unit 53 of the shooting console 5 to display a shooting order list screen on which a list of shooting order information is displayed on the display unit 54. Then, by operating the input unit 53, the shooting order information of the shooting target is specified from the shooting order list screen (step S1).

  Next, the operator attaches the FPD 9 to the bucky device 1 or the bucky device 2 and adjusts the orientation of the bucky device or the radiation source 3 to position the subject. Further, the operator console 6 sets the radiation irradiation condition based on the imaging region and issues a radiation irradiation instruction. In the radiation source 3, when a radiation irradiation instruction is received from the console 6, radiation irradiation is performed under the set radiation irradiation conditions (step S2).

  In the FPD 9, when radiation is irradiated from the radiation source 3, energy corresponding to the amount of irradiated radiation is accumulated as a charge amount by each detection element, and the charge accumulated in each detection element is read to obtain a medical image. Image data (RAW data) is generated and stored in the storage unit (step S3).

  Next, in the FPD 9, the control unit performs a reduction process on the medical image stored in the storage unit to generate a preview image (step S4). The preview image is obtained by reducing the image size of the medical image. Specifically, by thinning out the medical image at a predetermined thinning rate, a preview image composed of pixels at predetermined pixel intervals is generated. The generated image data of the preview image is transmitted to the imaging console 5 via the Bucky device or by wireless communication (step S5). Subsequently, the image data of the medical image stored in the storage unit is transmitted to the imaging console 5 via the Bucky device or by wireless communication (step S6). In the imaging console 5, the image data of the preview image and the medical image received via the communication I / F 55 is stored in the storage unit 52.

When the image data of the preview image is received via the communication I / F 55, the photographing console 5 performs correction processing and image processing on the preview image (step S7). In step S7, correction processing such as offset correction processing, gain correction processing, defective pixel correction processing, and lag (afterimage) correction processing using the dark image described above based on the characteristic information of the FPD 9 stored in the storage unit 52. Is done as needed. Further, as the image processing, gradation processing, frequency enhancement processing, grain suppression processing, and the like corresponding to the imaging region are performed.
If there are a plurality of FPDs 9, the characteristic information is stored in the storage unit 52 in association with the identification ID of each FPD 9, and the identification ID is acquired from the FPD 9 via the used Bucky device. Correction processing and image processing may be performed based on the characteristic information corresponding to the identified ID.

  Next, an image confirmation screen on which a preview image is displayed is displayed on the display unit 54 (step S8). The image confirmation screen displayed in step S8 is a screen on which a preview image is displayed. Although not particularly illustrated, the enlarged display frame 541a and the mark 541b in the positioning warning screen 541 shown in FIG. 8 are not displayed here. It is a screen. Other screen layouts and displayed buttons are the same as those of the positioning warning screen 541.

  Here, whether or not the image is suitable for a doctor's diagnosis is determined based on, for example, the quality of positioning, the presence or absence of body movement, the quality of radiation irradiation dose, the quality of image processing conditions, and the like. However, since the preview image is inferior to the medical image for diagnosis in resolution and image quality, an image that needs to be re-photographed may be missed due to poor positioning or body movement. If the image confirmation is performed with more care in order to reduce the risk of oversight, the time required for the confirmation increases, which increases the time for the patient to maintain positioning and increases the burden.

  Therefore, in step S9, by analyzing the preview image, the photographed medical image satisfies a predetermined criterion as a diagnostic medical image (an image satisfying the criterion as a diagnostic medical image). An image determination process for determining whether or not is is performed (step S9). Here, as the image determination process in step S9, a positioning determination process, a body movement determination process, a dose determination process, an image processing condition determination process described below, or a combination thereof is executed. In the following description of each process, a case where a preview image with a lung field as a subject is used as an embodiment will be described. However, image determination can be performed by a similar method in other imaging regions.

  First, the positioning determination process will be described. FIG. 4 shows a flowchart of the positioning determination process. The positioning determination process determines whether or not a specific part is missing in the medical image taken based on the preview image. If the specific part is defective, it is determined that the positioning is defective. This is a warning process. The positioning determination process is executed in cooperation with the control unit 51 and a program stored in the storage unit 52.

  First, processing for recognizing the range of the irradiation field in the preview image is performed (step S201). In this processing, a part where the radiation did not reach the imaging surface of the FPD 9 from the radiation source 3 is detected by masking during imaging, and the remaining part excluding the detected part from the preview image is set as an irradiation field. . This irradiation field setting processing can be performed by, for example, a method of detecting and excluding an area where the signal value of a pixel is substantially minimum (that is, the radiation dose is minimum) continuously inward from the contour of the image. .

  Next, the identified irradiation field is divided into a plurality of small areas, and among these divided small areas, a partial area within a predetermined range from the boundary of the irradiation field (the boundary between the irradiation field and the outside of the irradiation field) A process of extracting a pre-designated feature amount from each small region included in is performed (step S202). In the process of step S202, specifically, as shown in FIG. 5A, for example, the irradiation field is divided into small regions arranged in a 10 × 10 matrix. And in the four partial areas (upper end area R1, lower end area R2, left end area R3, right end area R4 in FIG. 5A), two rows each from the upper and lower boundary lines of the irradiation field, and two columns from the left and right boundary lines, respectively. The feature amount is extracted from the signal value of each small area included in each partial area. Specifically, since the lower end region R2 in FIG. 5A includes 1 to 20 small regions shown in FIG. 5B, 20 feature amounts are calculated. The calculation result is held as a data array indicating the position and feature amount of each small region. The same applies to the upper end region R1, the left end region R3, and the right end region R4. The feature amount calculated in step S202 is referred to herein as a data arrangement feature amount.

  Here, by dividing the partial region in contact with the boundary line into a plurality of rows or columns instead of only one row or one column, the image determination can be performed accurately even in the case of a complex image pattern. For example, when gas is reflected in the lower part of the lower end of the lung field, water is accumulated at the lower end of the lung field, or a catheter is inserted near the lower end of the lung field. Also in this case, it is possible to appropriately perform the determination by using the determination unit 51a learned based on the data of the small regions of a plurality of rows and a plurality of columns.

  The feature amount extracted in the process of step S202 is, for example, the maximum value (that is, the measured radiation intensity having the maximum measured value) among the signal values of each pixel in each small region. In addition, as other feature quantities, the maximum value of the first derivative of the signal value in each small area, and in particular, the maximum in each small area of the component of the first derivative that is parallel to the boundary of the irradiation field. A value and a coordinate value that takes the maximum value of the primary differential amount can be used. Alternatively, a power spectrum of luminance values can be used as the feature amount. In particular, a power spectral density in a direction parallel to the boundary line of the irradiation field and a frequency (wavelength) value that takes a maximum value can be used.

  When the feature amount is extracted, positioning determination is performed for each boundary line using the extracted feature amount (step S203). The positioning determination in step S203 is to determine whether or not the subject is missing from each boundary line using the determination unit 51a. In the example of FIG. 5A, the feature amount calculated in step S202 is acquired from the upper end region R1, the lower end region R2, the left end region R3, and the right end region R4, and these data are input to the determiner 51a of the control unit 51. In the determination device 51a, it is determined whether or not there is a portion where the lung field protrudes from each boundary line and is missing.

  The determiner 51a used for the positioning determination is learned in advance using a predetermined learning algorithm, and based on the learning result, whether or not there is a portion where the lung field protrudes from each boundary line and is missing. This determination is performed.

Here, a general concept of learning and determination by the learning algorithm will be described. Here, in order to simplify the description, a case where determination is performed using two feature amounts will be described as an example.
FIG. 6 is a graph plotting feature amounts calculated from a plurality of images (sample images) in which it is known in advance whether or not there is a lung field defect in a space around each feature amount used for positioning determination. . In the learning algorithm, as shown in FIG. 6, from the distribution of feature amounts calculated from a plurality of sample images, what kind of boundary line is drawn to distinguish an image having no lung field defect from an image having a lung field defect. It learns whether it can be performed, and creates a determinator that determines whether the image is a defect-free image or a defect image depending on which side of the boundary the feature value is located. Then, by inputting the feature amount calculated from the determination target image to the generated determination device, the determination device determines whether the image is an image having no lung field defect.

The learning algorithm used for learning by the determiner 51a is not particularly limited, but, for example, AdaBoost is used. AdaBoost is optimal by preparing a large number of data arrays of a plurality of feature amounts extracted from an image whose presence or absence of a subject is known in advance, and weighting and combining discriminators that determine subject loss. This is an algorithm for making a discriminator.

Here, the creation of the determinator 51a by learning and the determination in step S203 will be described using an example of using Adaboost as an example.
In step S203, positioning determination is performed for each boundary line between the vertical and horizontal irradiation fields. Therefore, the determiner 51a includes four types of determiners: an upper end determiner, a lower end determiner, a left end determiner, and a right end determiner.

(1) In creating the determination device 51a, first, a plurality of images in which lung fields are missing and images in which lung fields are not missing are prepared as sample images.
(2) Next, feature values similar to those in step S202 are calculated from all sample images. For example, the feature value (for example, maximum signal value) of the signal value of each small region included in each of the four partial regions in the upper end region R1, the lower end region R2, the left end region R3, and the right end region R4 illustrated in FIG. 5A is calculated. To do.

Next, for each of the upper end region R1, the lower end region R2, the left end region R3, and the right end region R4, by executing the following (3) to (4) using the calculated feature amount, the upper end determiner, the lower end region, Create a determiner, left edge determiner, and right edge determiner.
FIGS. 7A to 7D are diagrams schematically illustrating a process of creating a lower end determiner. 7A to 7D are two-dimensional feature quantity distributions created with the feature quantity 1 as the vertical axis and the feature quantity 2 as the horizontal axis. Here, in order to make the explanation easy to understand, the description is given by expressing in two dimensions using two feature quantities. However, since there are actually 20 data array feature quantities, a 20-dimensional feature quantity space having 20 axes is used. It becomes. In the following description, the process of creating the lower end determiner shown in FIGS. 7A to 7D will be described with reference to the drawings schematically showing the upper end determiner, the left end determiner, and the right end determiner. This is the creation process.

(3) First, a plurality of weak classifiers are created using a decision stamp. The weak discriminator is a discriminator that determines the presence or absence of a lung field defect based on whether or not a certain feature amount exceeds a preset threshold value. A plurality of weak discriminator devices having different threshold values are created for each feature amount.
For example, as shown in FIG. 7A, three weak classifiers with threshold values d1, d2, and d3 are created for feature quantity 1, and threshold values D1, D2, and D3 are set for feature quantity 2. Create two weak classifiers.

(4) Next, the weak classifier that contributes most to the determination of the presence or absence of lung field defects is selected. For example, as shown in FIG. 7B, the weak classifier D2 can correctly determine the 14 images excluding the three images surrounded by the circle A, and the ratio (number of images) of correctly determined images. Is the most common (high contribution). Therefore, the weak classifier D2 is selected as the weak classifier that contributes most to the determination of the presence or absence of lung field defects.
(5) Next, a weak classifier that contributes most to the determination of the presence or absence of lung field loss is selected by weighting the feature amount of the image that has failed the determination. By weighting the failed images, it is possible to select a weak classifier that can accurately determine an image that has failed in the previous weak classifier D2. For example, as shown in FIG. 7C, when the weight of the image that failed to be determined in FIG. 7B (the image corresponding to the point surrounded by the circle A) is increased and the other weights are reduced, The contribution of the weak classifier d2 is the highest. As a result, the weak classifier d2 is selected.
(6) The above (5) is repeated until there are no failed images, and a weak discriminator selected in each process is combined to create a discriminator. In FIG. 7D, a determiner is created by combining the weak classifier D2 and the weak classifier d2. However, since the contribution levels of the weak classifiers are different, the weak classifiers are weighted based on the correct answer rate of each weak classifier (the ratio of the image that can be correctly determined to the entire image).

  In step S203, an upper, lower, left, right image of the captured medical image is determined using the determiner 51a including the respective determiners (four determiners, upper, lower, left, and right) created by the learning. It is determined whether or not there is a lung field defect at each lung field edge. Specifically, in step S202, the feature amounts calculated from each of the upper end region R1, the lower end region R2, the left end region R3, and the right end region R4 are used as the upper end determiner, the lower end determiner, the left end determiner, and the right end determiner, respectively. , The determiner 51a determines the presence or absence of a lung field defect at the boundary between the upper, lower, left, and right irradiation fields.

As other learning algorithms, for example, a support vector machine or a neural network, or a K-nearest neighbor discriminator can be used. Statistical methods such as discriminant analysis may also be applied (reference: CM Bishop, “Pattern Recognition and Machine Learning”, Springer-Verlag, New Ed edition (2006)).
On the other hand, the support vector machine maps the data point indicated by the combination (feature vector) of the plurality of feature amounts extracted in the process of step S202 to the high-dimensional space, and the specific part is missing in the mapped high-dimensional space. This is a statistical algorithm that obtains a separation plane that linearly separates a certain image from an image having no defect, that is, has a maximum margin.

As a result of the positioning determination, if it is determined that the captured medical image is an image having a defect in a specific part (positioning failure) (step S204; YES), a positioning warning screen 541 is displayed on the display unit 54. (Step S205).
FIG. 8 shows an example of the positioning warning screen 541. As shown in FIG. 8, on the positioning warning screen 541, a frame 541b indicating a defective portion of the image is superimposed on the preview image PV, and a mark 541b indicating that there is a warning is displayed. Yes. In addition, the positioning warning screen 541 displays an output button B1, a re-shooting button B2, and a viewer button B3. The output button B1 is a button for instructing to output and save a medical image corresponding to the displayed preview image to the server device 10 as a diagnostic medical image. The re-imaging button B2 is a button for instructing to discard the medical image corresponding to the displayed preview image and perform re-imaging. The viewer button B3 is a button for instructing to generate a diagnostic medical image by performing correction processing and image processing on the medical image corresponding to the preview image.
After the positioning determination process, another image determination process is executed, or the process proceeds to step S10 in FIG.

  Next, the body movement determination process will be described. FIG. 9 shows a flowchart of the body movement determination process. Based on the preview image, the body movement determination process determines whether or not the body movement of the subject exists in the captured medical image, and warns when it is determined that the body movement of the subject exists. This is the process to be performed. The body movement determination process is executed in cooperation with the control unit 51 and a program stored in the storage unit 52.

First, an overview of the algorithm of the body movement determination process shown in FIG. 9 will be described with reference to FIGS. 10A to 10C and FIG.
10A to 10C are diagrams schematically illustrating a spatial frequency response (response) in a medical image.
10A to 10C, the horizontal axis is an axis indicating a spatial frequency band in the horizontal direction, and the vertical axis is an axis indicating a spatial frequency band in the vertical direction. In both axes, the center is the lowest frequency band, and the farther from the origin (center), the higher the spatial frequency band. In FIG. 10A to FIG. 10C, the intensity of the response in each spatial frequency band is shown by shading, and the stronger the response, the darker the density.

FIG. 10A is a diagram schematically illustrating a spatial frequency response in a still image. As shown in FIG. 10A, in the still image, the response of the high spatial frequency is approximately the same in each direction on average.
FIG. 10B is a diagram schematically illustrating a spatial frequency response in a still image (body motion image) having body motion in the horizontal direction. In the body motion image, the response of the spatial frequency in the body motion direction is weakened, and the strength of the response changes depending on the direction. When there is a body movement in the lateral direction, the spatial frequency response in the lateral direction becomes weak as shown in FIG. 10B.
FIG. 10C is a diagram schematically illustrating a spatial frequency response in an image including a lateral edge. FIG. 11 is a diagram illustrating the relationship between the vertical spatial frequency and the response in an image including a horizontal edge and an image including no edge. As shown in FIG. 10C, in an image including an edge, a strong high spatial frequency is generated in the direction perpendicular to the edge, and the strength of the response varies depending on the direction. Further, as shown in FIG. 11, an image including an edge has a higher response in the high-frequency spatial frequency band than an image not including an edge.
In the algorithm of the body motion determination process shown in FIG. 9, the presence or absence of body motion is determined based on the characteristics of the spatial frequency response in these still images, body motion images, and edge images.

  In the body movement determination process, first, a preview image to be subjected to the body movement determination process is divided into a plurality of small areas (for example, a rectangular area of 2 mm × 2 mm) (step S301). By dividing the medical image to be processed into small regions, the region in the lung field that is the subject region included in the medical image is also divided into small regions.

Next, an area within the lung field (lung field area) is extracted (step S302).
There are roughly three peaks in the histogram of signal values of still images taken of the chest. Appearing in the high signal area is a direct X-ray area in which X-rays are detected directly without passing through the subject, and appearing in the low signal side is in a trunk area such as a heart or bone with low X-ray transmittance. is there. Appearing between them is a lung field region that penetrates the lungs. Therefore, in step S302, the threshold value of the trunk region and the lung field region (low signal side threshold value 1) and the direct X-ray region threshold value (high signal) by discriminant analysis or the like from the signal value histogram of the processing target preview image. Side threshold values 2) are obtained, and regions having signal values between threshold values 1 and 2 are extracted as lung field regions. FIG. 12 shows an example of the lung field region extracted in step S302. A region L surrounded by a thick dotted line is a lung field region.
As a result, the extracted region in the lung field only needs to be divided into a plurality of small regions. For example, steps S301 and S302 are performed in the reverse order to extract the region in the lung field first, and the extracted lung The field area may be divided into a plurality of small areas.

Next, a local region not including an edge is extracted from the extracted lung field region (step S303).
In a region including an edge such as a rib, as described above, many high spatial frequency components are included. Therefore, in step S303, first, a high spatial frequency component is extracted by allowing each small region in the lung field region to pass through a high-pass filter that extracts only a high spatial frequency component in a predetermined band. Next, the maximum value or integral value of the response in the band (see FIGS. 11 and 13) between the Nyquist frequencies fN and fN−Δf (Δf is a predetermined value) in the extracted high spatial frequency component is calculated, Either the calculated maximum value or the integral value is compared with a threshold value set in advance for each value. If the calculated value is larger than the threshold value, it is determined that an edge is included in the small area. Here, since an area not including an edge is extracted, either the calculated maximum value or the integral value is compared with a threshold value set in advance for each value, and a small area equal to or smaller than the threshold value is defined as a local area that does not include an edge. Extracted. FIG. 14 shows a local region that does not include an edge extracted in step S303. A small area P in the figure is the extracted local area. In FIG. 14, only a part of the small region P is pointed out, but the small region surrounded by a rectangle having the same line type / size is the small region P. Note that the edge detection may use another method (for example, a method using a vertical profile or a horizontal profile of a preview image).

Next, in each extracted local region, an index value representing the response of the high spatial frequency component for each direction is calculated (step S304).
As shown in FIG. 15, the high spatial frequency component in the vertical direction is between −Δfw / 2 and Δfw / 2 (Δfw is a predetermined value) in the horizontal spatial frequency, and in the vertical spatial frequency. The response of each band (band included in Ah shown in FIG. 15) surrounded by the Nyquist frequency fN and fN−Δfb (Δfb is a predetermined value) is acquired, and the maximum value or the integrated value is obtained in the vertical direction. Is calculated as a response index Rh of the high spatial frequency component.
As shown in FIG. 15, the high spatial frequency component in the horizontal direction is between −Δfw / 2 and Δfw / 2 in the vertical spatial frequency and between the Nyquist frequencies fN and fN−Δfb in the horizontal spatial frequency. The response of each band (band included in Aw shown in FIG. 15) is acquired, and the maximum value or integral value is calculated as the response index Rw of the high spatial frequency component in the horizontal direction.
Here, an integral value is used. Here, the description is limited to the vertical and horizontal two-directional bands, but the response index values may be calculated in the four-directional bands to which diagonal two directions Au and Ad shown in FIG. 16 are further added.

Next, based on the response index value calculated for each local region, a body motion feature value is calculated, and based on the calculated body motion feature value, the presence or absence of a subject motion in the captured medical image is determined. (Step S305).
In step S305, as shown in FIG. 17, first, average values Rh ′ and Rw ′ are calculated for each direction for the responses Rh and Rw for each direction calculated for each local region. Next, the absolute value | R′h−R′w | of the calculated difference value of Rh ′ and Rw ′ is calculated as a body motion feature amount, and when this body motion feature amount is larger than a predetermined threshold value, It is determined that there is a body movement in a direction in which the numerical value is small (lateral direction in FIG. 17). In addition, in the case of four directions with two diagonal directions added, an average value is calculated for each direction for the response index for each direction calculated for each local region, and the difference value between the average value in the vertical direction and the horizontal direction The absolute value of the difference between the absolute value of and the average value in the oblique direction is calculated, and the larger value is used as the body movement feature amount.

As a result of the body movement determination, when it is determined that there is a body movement of the subject in the captured medical image (step S306; YES), the body movement is based on the position information of the local region not including the edge and the high spatial frequency component. An enlargement area for enlarging and displaying the portion is determined (step S307).
18A to 18C show an enlarged region determination process in step S307. As shown in FIG. 18A, first, a plurality of enlargement candidate regions (region 1 and region 2 in FIG. 18A) having a predetermined size are set in the lung field region. Next, as shown in FIG. 18B, the total of the body motion feature amounts calculated from the local regions in each expansion candidate region is acquired. Then, as illustrated in FIG. 18C, an enlargement candidate region (region 2 in FIGS. 18A and 18B) having the largest total body motion feature amount is determined as the enlargement region.

Next, a body movement warning screen 542 in which the determined enlarged area is displayed in an enlarged manner is displayed on the display unit 54 (step S308).
FIG. 19 shows an example of the body motion warning screen 542. On the body movement warning screen 542, a frame 542a indicating the determined enlarged area is superimposed on the preview image, and an enlarged image obtained by enlarging the enlarged area and “there is a possibility of body movement”. A screen 542b on which a warning message is displayed pops up. The body motion warning screen 542 displays an output button B1, a re-shooting button B2, and a viewer button B3. The output button B1 is a button for instructing to output and save a medical image corresponding to the preview image to the server device 10. The re-photograph button B2 is a button for instructing to discard the medical image corresponding to the preview image and perform re-photographing. The viewer button B3 is a button for instructing to generate a diagnostic medical image by performing correction processing and image processing on the medical image corresponding to the preview image.
After the body movement determination process, another image determination process is executed, or the process proceeds to step S10 in FIG.

  Next, the dose determination process will be described. FIG. 20 shows a flowchart of the dose determination process. The dose determination process is a process that determines whether or not the radiation dose at the time of taking a medical image exceeds a predetermined standard, and gives a warning when it is determined that the dose has not exceeded (dose is insufficient). is there. The dose determination process is executed in cooperation with the program stored in the control unit 51 and the storage unit 52. This dose determination processing is performed based on a preview image that has not been subjected to correction processing or image processing.

  First, a preview image stored in the storage unit 52 and not subjected to correction processing / image processing is read out, and a region of interest is set (step S401). In the image obtained by photographing the front of the chest, a rectangular region including the lung field is set as the region of interest. For example, a lung field region is extracted by the above-described method, and a rectangular region surrounding the extracted lung field region is set as a region of interest.

Next, an average value, a maximum value, or a minimum value of signal values of pixels in the region of interest is calculated (step S402).
Next, the calculated average value, maximum value, or minimum value is compared with a threshold value set in advance for each value, and if the threshold value is exceeded, it is determined that the radiation dose exceeds a predetermined standard. The When the calculated average value, maximum value, or minimum value is less than or equal to a threshold value set in advance for each value, it is determined that the radiation dose does not exceed a predetermined standard, that is, the dose is insufficient. (Step S403).
In addition, each of the average value, the maximum value, and the minimum value of the signal values of the pixels in the region of interest is compared with a threshold value set in advance for each value. It is good.

When it is determined that the dose is insufficient (step S404; YES), a dose warning screen 543 is displayed on the display unit 54 (step S405).
FIG. 21 shows an example of the dose warning screen 543. On the dose warning screen 543, a frame 543a indicating the set region of interest is superimposed on the preview image, a mark 543b indicating that there is an abnormality, and a “dose abnormality” message 543c. In addition, an output button B1, a re-imaging button B2, and a viewer button B3 are displayed on the dose warning screen 543. The output button B1 is a button for instructing to output and save the displayed medical image to the server device 10. The re-imaging button B2 is a button for instructing to discard the displayed medical image and perform re-imaging. The viewer button B3 is a button for instructing to generate a diagnostic medical image by performing correction processing and image processing on the medical image corresponding to the preview image.
After the dose determination process, another image determination process is executed, or the process proceeds to step S10 in FIG.

  Next, the image processing condition determination process will be described. FIG. 22 is a flowchart of the image processing condition determination process. The image processing condition determination process determines whether the image processing condition of the image processing applied to the captured medical image is appropriate based on the image processing condition applied to the preview image. This is a process for giving a warning when it is determined. The image processing condition determination process is executed in cooperation with the control unit 51 and a program stored in the storage unit 52.

  First, a region of interest is set in the preview image (step S501). In the image obtained by photographing the front of the chest, a rectangular region including the lung field is set as the region of interest. For example, a lung field region is extracted by the above-described method, and a rectangular region surrounding the extracted lung field region is set as a region of interest.

Next, an average value, a maximum value, and a minimum value of signal values of pixels in the region of interest are calculated (step S502).
Next, the calculated average value, maximum value, and minimum value are respectively compared with threshold values set in advance, and based on the comparison result, the image processing conditions for image processing applied to the captured medical image are appropriate. It is determined whether or not (step S503).
Here, it is mainly determined whether or not the image processing conditions for gradation processing are appropriate. When the calculated average value or maximum value is larger than a predetermined threshold value, for example, the lung field signal is blacked out, so it is determined that the image processing conditions are not appropriate. If the calculated minimum value is smaller than a predetermined threshold value, it is determined that the image processing condition is not appropriate because the heart region is flying white.

If it is determined that the image processing conditions are not appropriate (step S504; YES), an image processing warning screen 544 is displayed on the display unit 54 (step S505).
FIG. 23 shows an example of the image processing warning screen 544. On the image processing warning screen 544, a mark 544a indicating that the image processing condition is not appropriate and a message 544b indicating that “image processing” is not appropriate are displayed on the preview image. The image processing warning screen 544 displays an output button B1, a re-shooting button B2, and a viewer button B3. The output button B1 is a button for instructing to output and save a medical image corresponding to the displayed preview image to the server device 10. The re-imaging button B2 is a button for instructing to discard the medical image corresponding to the displayed preview image and perform re-imaging. The viewer button B3 is a button for instructing to generate a diagnostic medical image by performing correction processing and image processing on the medical image corresponding to the preview image.
After the image processing condition determination process, another image determination process is executed, or the process proceeds to step S10 in FIG.

  When the image determination is performed by combining the positioning determination process, the body movement determination process, the dose determination process, and the image processing condition determination process, the warning screen is preferably integrated and displayed on one screen. That is, it is preferable to display a frame, a mark, a screen, and the like to be displayed on each warning screen on one warning screen.

  In step S10 of FIG. 3, it is determined whether or not the re-shooting button B2 is pressed by the input unit 53. When it is determined by the input unit 53 that the re-imaging button B2 has been pressed (step S10; YES), the preview image to be processed and the corresponding medical image are deleted from the storage unit 52 (step S11). The process returns to step S2. On the other hand, if the re-imaging button B2 is not pressed by the input unit 53 (step S10; NO) and the display of the medical image for diagnosis is instructed by pressing the viewer button B3 (step S12; YES), the memory is stored. The medical image stored in the unit 52 is read out and subjected to correction processing and image processing to generate a medical image for diagnosis (step S13), and the medical image for diagnosis is displayed on the display unit 54. (Step S14). Correction processing and image processing are performed in substantially the same manner as the preview image (processing under substantially the same image processing conditions). When the output button B1 is pressed (step S15; YES), the image data of the diagnostic medical image is transmitted to the server device 10 in association with the imaging order information specified in step S1 by the network communication unit 56 ( Step S16), the medical image generation process ends. In the server device 10, the received image data of the medical image is stored in the database in association with the imaging order information.

In this way, the imaging console 5 uses the preview image, which is a reduced image of the captured medical image, and the medical image satisfies the predetermined criteria as a diagnostic medical image (suitable for diagnosis). If it is determined that the image is not satisfied, a warning screen that warns that is displayed on the display unit 54. Therefore, if an improperly defective image is taken for diagnosis, a warning is given immediately after taking the image, so that the imaging engineer can immediately recognize the improperly improperly used image for diagnosis, and overlook the defective image. Can be prevented. In addition, since a warning when a defective image is taken is immediately warned, it takes less time than a conventional imaging technician to check visually, so the patient can keep the positioning time short. . In addition, it is not necessary to cancel positioning once during the time required for the image determination process, so even if re-shooting is performed, it is only necessary to fine-tune the positioning and shooting conditions, greatly reducing the burden on the radiographer and patient. Can do.
In addition, by highlighting or enlarging the area to be confirmed in the preview image, even if the preview image has a small console and poor resolution and image quality, the confirmation work becomes easy and required for confirmation. Time and work load can be greatly reduced.

  In the above embodiment, the case where the present invention is applied to the medical image photographing system 100 installed in the photographing room Rm has been described as an example. However, as described below, medical images for patients that are difficult to move are described. The present invention can also be applied to the imaging system 200.

  As shown in FIG. 24, the medical imaging system 200 is brought into the hospital room Rc or the like together with the roundabout wheel 7P, and the FPD cassette 9P is placed between the bed B and a specific part of the body of the patient H sleeping on the bed B, for example. In this state, the medical image is generated by irradiating the portable radiation source 3P with radiation from the portable radiation source 3P.

  As shown in FIG. 24, the medical imaging system 200 has a portable radiation source 3P and an operation console 6P mounted on a roundabout car 7P, and is carried by an access point AP1 provided on the roundabout car 7P. A possible console 5P and FPD cassette 9P can be wirelessly connected.

  The radiation source 3P includes the console 6P, the console 5P, and the FPD 9P except that the radiation source 3P is portable (for example, downsized). The imaging console 5 and the FPD 9 basically have the same configuration and functions, and the medical image generation process shown in FIG. 3 can be executed between these apparatuses.

  That is, at the roundabout, first, an operator such as a radiographer operates the input unit of the console 5P to display a radiographing order list screen for displaying a list of radiographing order information on the display unit. Then, by operating the input unit, the shooting order information of the shooting target is designated from the shooting order list screen.

  Next, the operator inserts the FPD 9P between a specific part of the body of the patient H sleeping on the bed B and the bed B, and adjusts the position and orientation of the radiation source 3P to position the subject. In addition, the operator console 6 </ b> P sets radiation irradiation conditions based on the imaging region, and issues a radiation irradiation instruction. In the radiation source 3P, when a radiation irradiation instruction is received from the console 6P, radiation irradiation is performed under the set radiation irradiation conditions.

  In the FPD 9P, when radiation is irradiated from the radiation source 3P, energy corresponding to the amount of irradiated radiation is accumulated as a charge amount by each detection element, and the charge accumulated in each detection element is read to obtain a medical image. Image data (RAW data) is generated and stored in the storage unit.

  Next, in the FPD 9P, the control unit generates a reduced image (preview image) from the medical image stored in the storage unit. The generated image data of the preview image is transmitted to the console 5P by wireless communication. Subsequently, the image data of the medical image stored in the storage unit is transmitted to the console 5P by wireless communication.

  In the console 5P, when the image data of the preview image and the medical image is received, the received image data of the preview image and the medical image is stored in the storage unit. Then, correction processing and image processing are performed on the preview image. The contents of the correction process and the image process are as described above.

  Next, an image confirmation screen on which a preview image is displayed is displayed on the display unit of the console 5P. Further, the preview image is analyzed, and an image determination process for determining whether the taken medical image is a diagnostic medical image is executed. As described above, as the image determination process, a positioning determination process, a body movement determination process, a dose determination process, an image processing condition determination process, or a combination thereof is executed. When it is determined that the medical image is not suitable for diagnosis, a warning screen indicating the determination result is displayed on the display unit of the console 5P. The warning screen displayed on the console 5P is a screen as shown in FIG. 8, FIG. 19, FIG. 21, or FIG. 23, and highlights or enlarges a portion having a defect or a body motion. It is possible to do.

Here, since a portable console has a small screen for easy carrying, image confirmation has been difficult in comparison with a stationary console.
On the other hand, the console 5P determines whether or not the medical image is an image suitable for diagnosis using a preview image that is a reduced image of the captured medical image, and is not a medical image suitable for diagnosis. Is determined, a warning screen indicating the determination result is displayed on the display unit. Therefore, even with a small screen for round trips, the imaging engineer can immediately recognize a defective image that is inappropriate for diagnosis, and can prevent the defective image from being overlooked. Further, since a warning when a defective image is taken is immediately warned, it takes a shorter time compared with a case where a photographing engineer visually confirms a conventional image. As a result, it is possible to reduce the time that a serious patient maintains positioning. In addition, since the waiting time for the image determination process is short and there is no need to cancel positioning, it is only necessary to fine-tune the positioning and imaging conditions even when re-imaging is performed, greatly reducing the burden on the imaging technician and patient. be able to.
In addition, by highlighting or enlarging the area to be confirmed in the preview image, even if the preview image has a small console and poor resolution and image quality, the confirmation work becomes easy and required for confirmation. Time and work load can be greatly reduced.

  When re-imaging is instructed from the input unit on the console 5P, the preview image to be processed and the corresponding medical image are deleted from the storage unit 52. If re-imaging is not instructed, the medical image may be subjected to correction processing or image processing on the console 5P and displayed and transmitted to the server device 10, or the image data of the medical image may be transferred to the console 5P or the like. Alternatively, the medical image may be displayed after being subjected to correction processing or image processing on the console 5 </ b> P or the like and transmitted to the server device 10.

As described above, according to the medical image capturing system 100, the FPD 9 captures a specific part of the human body as a subject to generate a medical image that is a still image and a preview image that is a reduced version of this medical image. Send to 5. The control unit 51 of the photographing console 5 analyzes the preview image to determine whether or not the photographed medical image satisfies a predetermined criterion as a diagnostic medical image, and as a diagnostic medical image. If it is determined that the predetermined standard is not satisfied, a warning is displayed on the display unit 54.
Therefore, if a defective image that does not meet the predetermined criteria as a medical image for diagnosis is taken, a warning is issued immediately after the image is taken, so that the imaging engineer immediately recognizes an improper defective image for diagnosis. It is possible to prevent a defective image from being overlooked. In addition, the time for the patient to maintain the positioning can be shortened, and the burden on the patient can be reduced.

  Specifically, whether the captured medical image is an image without a specific part defect, whether the subject does not have body motion, and the radiation dose at the time of imaging is determined in advance. It is possible to determine at least one of whether the image exceeds the reference and whether the image processing condition is an appropriate image.

In addition, the said embodiment is a suitable example of this invention, and is not limited to this.
For example, in the above-described embodiment, the medical image is reduced on the FPD side. However, the medical image may be reduced on the imaging console 5 side.
In the above embodiment, the medical image capturing system that generates a medical image using FPD has been described as an example. However, the means for generating a medical image is not limited to this, and for example, CR is used. Also good.

  In the above description, an example in which an HDD or a semiconductor nonvolatile memory is used as a computer-readable medium for the program according to the present invention is disclosed, but the present invention is not limited to this example. As another computer-readable medium, a portable recording medium such as a CD-ROM can be applied. Further, a carrier wave is also applied as a medium for providing program data according to the present invention via a communication line.

  In addition, the detailed configuration and detailed operation of each device constituting the medical image photographing system can be changed as appropriate without departing from the spirit of the invention.

100 Medical Imaging System 1 Bucky Device 2 Bucky Device 3 Radiation Source 5 Imaging Console 51 Control Unit 52 Storage Unit 53 Input Unit 54 Display Unit 55 Communication I / F
56 Network communication section 57 Bus 6 Console 7 HIS / RIS
8 Diagnosis console 9 FPD
10 Server device

Claims (5)

Image generating means for generating a medical image as a still image by photographing a specific part of the human body as a subject;
Preview image generating means for generating a preview image by reducing the medical image;
Display means for displaying the preview image;
Image determination means for determining whether or not the medical image satisfies a predetermined criterion as a medical image for diagnosis by analyzing the preview image;
Control means for displaying a warning on the display means when the image determination means determines that the medical image does not satisfy a predetermined criterion as a diagnostic medical image;
A medical imaging system comprising:   The image determination means analyzes the preview image to determine whether the medical image is an image without a defect of the specific part, whether the subject has no body movement, The medical image photographing system according to claim 1, wherein at least one of whether or not the image is an image in which the radiation exposure amount exceeds a predetermined reference is determined. Image processing means for performing image processing on the preview image;
The image determination unit analyzes the preview image or the preview image image-processed by the image processing unit to determine whether the medical image is an image having no defect in the specific part. At least one of whether the image has no motion, whether the radiation dose at the time of imaging exceeds a predetermined standard, and whether the image processing condition is an appropriate image. The medical image photographing system according to claim 1, wherein one is determined. An image processing apparatus connected to an image generation means for generating a medical image that is a still image and a preview image obtained by reducing the medical image by photographing a specific part of a human body as a subject, so that data can be transmitted and received.
Display means for displaying the preview image;
Analyzing the preview image to determine whether the medical image is an image satisfying a predetermined criterion;
Control means for displaying a warning on the display means when the image determination means determines that the medical image does not satisfy a predetermined criterion as a diagnostic medical image;
A medical image processing apparatus comprising: A computer used for a medical image processing apparatus connected to be capable of transmitting and receiving data with a medical image that is a still image by capturing a specific part of the human body as a subject and an image generating unit that generates a preview image obtained by reducing the medical image,
Display means for displaying the preview image;
Image determination means for determining whether or not the medical image is an image satisfying a predetermined criterion by analyzing the preview image;
Control means for displaying a warning on the display means when the image determination means determines that the medical image does not satisfy a predetermined criterion as a diagnostic medical image;
Program to function as.

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