JP7381282B2 - Image processing device - Google Patents

Description

Embodiments of the present invention relate to an image processing device.

Conventionally, a technique for correcting the contrast of a magnetic resonance image is known in order to make the tissue depicted in the magnetic resonance image easier to see. In particular, clarifying the contrast of a region of interest on a magnetic resonance image facilitates interpretation by a doctor or the like.

However, since the pixel values of a magnetic resonance image vary depending on the imaging environment, the imaging site, etc., it may be necessary to adjust the values of parameters that define the contrast of the magnetic resonance image for each examination or imaging. Therefore, the operator's working time may become longer.

Japanese Patent Application Publication No. 2010-142462

The problem to be solved by the present invention is to facilitate contrast adjustment according to a region of interest in a magnetic resonance image by an operator.

The image processing device according to the embodiment includes a specifying section, a receiving section, and a display control section. The specifying unit specifies, in accordance with a region of interest on a magnetic resonance image taken of the subject, a region that accepts adjustment by an operator in tone information representing a relationship between an MR signal value and brightness. The accepting unit accepts a change in the relationship between the MR signal value and the brightness in the area specified by the specifying unit. The display control unit has a first operation screen that accepts a contrast adjustment process in a magnetic resonance image corresponding to a change , a second operation screen that accepts a pixel value adjustment process of the entire magnetic resonance image , and a previous brightness adjustment screen. A selectable selection screen indicating whether or not to apply the value of a parameter defining the brightness of the magnetic resonance image adjusted by the processing to the brightness adjustment of the newly captured magnetic resonance image is displayed on the display unit. .

FIG. 1 is a block diagram showing an example of the configuration of an MRI apparatus according to the first embodiment. FIG. 2 is a graph showing an example of gradation information according to the first embodiment. FIG. 3 is a diagram illustrating an example of adjustment regions for each anatomical type of tissue according to the first embodiment. FIG. 4 is a diagram showing an example of the first operation screen according to the first embodiment. FIG. 5 is a diagram showing an example of the second operation screen according to the first embodiment. FIG. 6 is a diagram showing an example of the third operation screen according to the first embodiment. FIG. 7 is a flowchart illustrating an example of the flow of brightness adjustment processing according to the first embodiment. FIG. 8 is a diagram illustrating an example of options selectable by the operator according to the second embodiment. FIG. 9 is a diagram illustrating an example of reflection of parameter adjustment results for different protocols according to the second embodiment. FIG. 10 is a diagram illustrating an example of the overall configuration of a medical information system according to a modification.

Hereinafter, the first embodiment will be described in detail with reference to the drawings.

(First embodiment)
FIG. 1 is a block diagram showing an example of the configuration of an MRI (Magnetic Resonance Imaging) apparatus 100 according to the present embodiment. The MRI apparatus 100 is an example of an image processing apparatus according to this embodiment.

The MRI apparatus 100 includes a static magnetic field magnet 101, a gradient magnetic field coil 102, a gradient magnetic field power supply 103, a bed 104, a bed control circuit 105, a transmitting coil 106, a transmitting circuit 107, a receiving coil 108, and a receiving circuit. 109, a sequence control circuit 110, a computer system 120, and a gantry 150. Note that the MRI apparatus 100 does not include the subject P. The subject P is, for example, a patient imaged by the MRI apparatus 100.

The static magnetic field magnet 101 is a magnet formed in a hollow cylindrical shape (including one in which the cross section perpendicular to the axis of the cylinder is elliptical), and generates a uniform static magnetic field in the internal space.

The gradient magnetic field coil 102 is a coil formed in a hollow cylindrical shape (including a coil whose cross section perpendicular to the axis of the cylinder is elliptical), and generates a gradient magnetic field. The gradient magnetic field coil 102 is formed by combining three coils corresponding to the mutually orthogonal X, Y, and Z axes, and these three coils are individually supplied with current from the gradient magnetic field power supply 103. A gradient magnetic field whose magnetic field strength changes along each of the X, Y, and Z axes is generated.

The gradient magnetic field power supply 103 supplies current to the gradient magnetic field coil 102. For example, the gradient magnetic field power supply 103 individually supplies current to each of the three coils forming the gradient magnetic field coil 102.

The bed 104 includes a top plate 104a on which the subject P is placed, and under the control of the bed control circuit 105, the top plate 104a is placed in the cavity of the gradient magnetic field coil 102 (with the subject P placed thereon). (imaging port). The bed control circuit 105 is a processor that drives the bed 104 and moves the top plate 104a in the longitudinal direction and the vertical direction under the control of the computer system 120.

The transmitting coil 106 is arranged inside the gradient magnetic field coil 102, receives an RF (Radio Frequency) signal from the transmitting circuit 107, and applies a high frequency magnetic field to the subject P. The subject P is excited by applying a high frequency magnetic field by the transmitting coil 106.

Under the control of the sequence control circuit 110, the transmitting circuit 107 supplies the transmitting coil 106 with an RF pulse corresponding to the Larmor frequency determined by the type of target atomic nucleus and the strength of the magnetic field.

The receiving coil 108 is arranged inside the gradient magnetic field coil 102, and receives a magnetic resonance signal (hereinafter referred to as an MR signal) emitted from the subject P under the influence of a high-frequency magnetic field. Upon receiving the MR signal, the receiving coil 108 outputs the received MR signal to the receiving circuit 109. Note that in FIG. 1, the receiving coil 108 is provided separately from the transmitting coil 106, but this is an example, and the present invention is not limited to this configuration. For example, a configuration may be adopted in which the receiving coil 108 is also used as the transmitting coil 106.

The receiving circuit 109 performs analog-to-digital conversion on the analog MR signal output from the receiving coil 108 to generate MR data. Further, the receiving circuit 109 transmits the generated MR data to the sequence control circuit 110. Note that analog-to-digital conversion may be performed within the receiving coil 108. Further, the receiving circuit 109 can perform arbitrary signal processing other than analog-to-digital conversion.

The sequence control circuit 110 performs imaging of the subject P by controlling the gradient magnetic field power supply 103, the transmitting circuit 107, and the receiving circuit 109 based on sequence information transmitted from the computer system 120. Further, the sequence control circuit 110 receives MR data from the receiving circuit 109. Sequence control circuit 110 transfers the received MR data to computer system 120. The sequence control circuit 110 may be realized by, for example, a processor, or may be realized by a mixture of software and hardware.

Sequence information is information that defines a procedure for performing imaging. The sequence information is generated by the computer system 120 based on the imaging conditions for imaging the subject P.

The computer system 120 executes processes such as overall control of the MRI apparatus 100, data collection, and image reconstruction. Computer system 120 has a network interface 121, a storage circuit 122, a processing circuit 123, an input interface 124, and a display 125.

The network interface 121 transmits sequence information to the sequence control circuit 110 and receives MR data from the sequence control circuit 110. Further, MR data received by the network interface 121 is stored in the storage circuit 122.

The storage circuit 122 stores various programs. The storage circuit 122 is realized by, for example, a RAM (Random Access Memory), a semiconductor memory element such as a flash memory, a hard disk, an optical disk, or the like. Note that the storage circuit 122 is also used as a non-transitory hardware storage medium. The memory circuit 122 is an example of a memory section.

The input interface 124 accepts various instructions and information input from an operator such as a doctor or radiology technician. The input interface 124 is realized by, for example, a trackball, a switch button, a mouse, a keyboard, or the like.

Note that in this embodiment, the input interface 124 is not limited to one that includes physical operation components such as a mouse and a keyboard. For example, an electrical signal processing circuit that receives an electrical signal corresponding to an input operation from an external input device provided separately from the MRI apparatus 100 and outputs this electrical signal to the processing circuit 123 is also an example of the input interface 124. include.

The input interface 124 is connected to the processing circuit 123 , converts various input operations received from the operator into electrical signals, and outputs the electrical signals to the processing circuit 123 .

The display 125 displays various GUIs (Graphical User Interfaces), magnetic resonance images (MR images), various images generated by the processing circuit 123, etc. under the control of the processing circuit 123. Display 125 is an example of a display section.

The processing circuit 123 performs overall control of the MRI apparatus 100. More specifically, the processing circuit 123 includes a collection function 123a, a reconstruction function 123b, a reception function 123c, a gradation information generation function 123d, a specific function 123e, a display control function 123f, and an image correction function 123g. has. The collection function 123a is an example of a collection unit. The reconstruction function 123b is an example of a collection unit. The reception function 123c is an example of a reception unit. The gradation information generation function 123d is an example of a gradation information generation section. The specific function 123e is an example of a specific section. The display control function 123f is an example of a display control section. The image correction function 123g is an example of an image correction section.

Here, for example, each processing of a collection function 123a, a reconstruction function 123b, a reception function 123c, a gradation information generation function 123d, a specific function 123e, a display control function 123f, and an image correction function 123g, which are components of the processing circuit 123, is performed. The functions are stored in the storage circuit 122 in the form of programs executable by a computer. The processing circuit 123 reads each program from the storage circuit 122 and executes each read program, thereby realizing a function corresponding to each program. In other words, the processing circuit 123 in a state where each program is read has each function shown in the processing circuit 123 of FIG. In FIG. 1, the single processing circuit 123 includes a collection function 123a, a reconstruction function 123b, a reception function 123c, a gradation information generation function 123d, a specific function 123e, a display control function 123f, and an image correction function 123g. Although the above description has been made assuming that each processing function is realized, the processing circuit 123 may be configured by combining a plurality of independent processors, and each processor may realize each processing function by executing each program. .

The term "processor" used in the above description refers to, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (for example, Refers to circuits such as Simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD), and Field Programmable Gate Array (FPGA). Note that instead of storing the program in the storage circuit 122, the program may be directly incorporated into the circuit of the processor. In this case, the processor realizes its functions by reading and executing a program built into the circuit.

The collection function 123a collects MR data converted from the MR signal generated by the execution of the pulse sequences from the sequence control circuit 110 via the network interface 121 by executing various pulse sequences. For example, the collection function 123a generates sequence information based on imaging conditions, and sends the generated sequence information to the sequence control circuit 110 via the network interface 121.

Furthermore, the collection function 123a arranges the collected MR data according to the amount of phase encoding and the amount of frequency encoding given by the gradient magnetic field. MR data arranged in k-space is referred to as k-space data. The k-space data is stored in storage circuit 122.

The reconstruction function 123b generates a magnetic resonance image by performing reconstruction processing such as Fourier transformation on the k-space data stored in the storage circuit 122. The reconstruction function 123b stores the generated magnetic resonance image in the storage circuit 122. Hereinafter, the magnetic resonance image generated by the reconstruction function 123b will be referred to as an original image.

The reception function 123c receives various operations by the operator via the input interface 124. For example, the reception function 123c receives, via the input interface 124, an operation by an operator to specify a region of interest. Further, the reception function 123c receives an operation by the operator to change the contrast (gradation) or pixel value of the magnetic resonance image on the first to third operation screens described later. For example, the reception function 123c accepts a change in the relationship between the MR signal value and the brightness in the adjustment region specified by the specification function 123e, which will be described later. More specifically, the acceptance function 123c accepts an operation by an operator to change the slope or inflection point of the γ curve.

The reception function 123c sends information on parameters after changing the contrast or pixel values of the received region of interest or magnetic resonance image to the gradation information generation function 123d, the specific function 123e, the display control function 123f, or the image correction function 123g. do.

The gradation information generation function 123d generates gradation information representing the relationship between the MR signal value and the brightness in the magnetic resonance image generated by the reconstruction function 123b.

FIG. 2 is a graph showing an example of gradation information according to this embodiment. In both the upper and lower rows of FIG. 2, the horizontal axis represents the MR signal value, and the vertical axis represents the brightness in the magnetic resonance image.

The upper part of FIG. 2 is a graph showing the relationship between the MR signal value and brightness in the original image generated by the reconstruction function 123b.

In the original image whose contrast has not been adjusted, the relationship between the MR signal value and the brightness is represented by a linear graph in which the higher the MR signal value, the higher the brightness, as shown in the upper part of FIG.

In the relationship in which the MR signal value and the brightness are proportional as shown in the upper part of FIG. 2, the contrast between organs in the magnetic resonance image may be too small or too large, making interpretation difficult.

Therefore, the gradation information generation function 123d corrects the gradation information shown in the upper part of FIG. 2 to the gradation information shown in the lower part of FIG. 2. The correction processing performed by the gradation information generation function 123d is referred to as initial correction in order to distinguish it from the contrast and pixel value correction performed by the operator, which will be described later. Hereinafter, when gradation information is simply referred to, it refers to gradation information after initial correction.

As shown in the lower part of FIG. 2, the gradation information after the initial correction becomes a graph that draws an S-shaped upward-sloping curve. This graph is called a γ curve 80. The γ curve 80 is an example of gradation information according to this embodiment, and represents the relationship between MR signal value and brightness. The γ curve 80 is also referred to as a characteristic curve or a tone curve.

In the γ curve 80, the range A from the maximum MR signal value "m" to the MR signal value "n" is defined as a range A in which contrast does not disappear in the MR image and visualized organs and the like are visible.

The maximum value "m" of the MR signal value is the maximum value of the MR signal value in the original image generated by the reconstruction function 123b. Further, the MR signal value "n" may be set in advance, or may be changed depending on the maximum value "m" of the MR signal values.

Of the γ curve 80, the portion included in range A is divided into three regions, in order from the highest luminance to the shoulder region, linear region, and toe region. The straight portion is located at the center of the γ curve 80, and is a portion where the γ curve 80 is relatively straight. The shoulder portion has higher luminance and MR signal value than the straight portion, and has a gentler slope than the straight portion. The foot portion has lower luminance and MR signal value than the straight portion, and has a gentler slope than the straight portion.

The steeper the slope of the γ curve 80, the greater the degree of change in brightness relative to the change in MR signal value, and therefore the stronger the contrast of the magnetic resonance image.

The lower limit of the MR signal value at the foot is the MR signal value "n" which is the lower limit of range A. Further, the upper limit of the MR signal value at the shoulder portion is the MR signal value “m” which is the upper limit of range A. Further, in the example shown in the diagram of FIG. 2, the MR signal value at the boundary between the shoulder and the straight section is "f", and the MR signal value at the boundary between the straight section and the foot is "e". Further, the brightness value corresponding to the MR signal value “m” is “a”, the brightness value corresponding to the MR signal value “f” is “b”, the brightness value corresponding to the MR signal value “e” is “c”, Let the luminance value corresponding to the MR signal value "n" be "d". The values of “e”, “f”, “a”, “b”, “c”, and “d” are determined by the characteristics of the γ curve 80.

In this embodiment, the characteristics of the γ curve 80 are defined by, for example, an exponential function f(t, n, k, s).

It is assumed that the initial values of the parameters "t", "n", "k", and "s" are stored in the storage circuit 122, for example. The gradation information generation function 123d generates the γ curve 80 based on the initial value.

The parameter "t" is a threshold value that sets the pixel value to "0". The value of "t" is expressed as a percentage of the maximum pixel value. For example, when "t" is "0.01", the gradation information generation function 123d replaces pixel values less than or equal to the value obtained by multiplying the maximum pixel value by "0.01" with "0". The maximum pixel value is the maximum pixel value in the original image generated by the reconstruction function 123b.

Note that since the magnetic resonance image is a grayscale image, the pixel values do not include color information but only brightness information. For example, when the pixel value is "0", the pixel becomes black, and the larger the pixel value, the closer to white the pixel becomes. In other words, areas where the MR signal value is smaller than the value calculated by multiplying the maximum pixel value by the value of "t" are displayed in black on the magnetic resonance image, similar to areas where no MR signal value was obtained. be done.

The parameter “n” is the slope of the γ curve 80. Further, the parameter “k” represents the position of the inflection point of the γ curve 80.

Moreover, the parameter "s" is a magnification by which the maximum pixel value is multiplied. In the exponential function f(t, n, k, s), the value obtained by multiplying the maximum pixel value in the original image generated by the reconstruction function 123b by the parameter "s" is used as the maximum pixel value. The initial value of the parameter "s" is, for example, "1". When the parameter "s" = "1", the maximum pixel value in the original image generated by the reconstruction function 123b is used as the maximum pixel value in the exponential function f(t, n, k, s).

The gradation information generation function 123d stores the generated gradation information after initial correction, that is, information representing the correspondence between the MR signal value and the luminance value defined by the γ curve 80, in the storage circuit 122.

Returning to FIG. 1, the specific function 123e specifies a region in the γ curve 80 that accepts adjustment by the operator, depending on the region of interest on the magnetic resonance image taken of the subject P. In this embodiment, this area is referred to as an adjustment area.

The adjustment region is a range of the γ curve 80 in which the operator can change the γ curve 80. The operator can change the adjustment area on the first operation screen, which will be described later, and the details will be described later.

The range of possible values of the generated MR signal differs depending on the anatomical type of tissue. Therefore, when the γ curve 80 corresponding to the range of MR signal values generated from the tissue depicted in the region of interest is changed, the contrast of the region of interest on the magnetic resonance image changes. Therefore, the specifying function 123e specifies different adjustment regions 9 depending on the anatomical type of the tissue depicted in the region of interest.

In this embodiment, the anatomical types of tissues are classified into "vascular vascular system" and "real organ." Note that the method of classifying the organization is one example, and is not limited to this.

"Vascular vasculature" includes blood vessels and vessels. Moreover, a "parenchymal organ" is an organ whose cut surface is solid, and includes, for example, the kidney, liver, pancreas, and the like. Furthermore, in the brain, the cerebrum, cerebellum, brainstem, and spinal cord are included in the parenchymal organs. "Solid organs" are also called solid organs.

FIG. 3 is a diagram showing an example of adjustment regions for each anatomical type of tissue according to the present embodiment. During magnetic resonance imaging, signal values of MR signals generated from parenchymal organs are mainly included in range B shown in FIG. 3 . The MR signal values in range B correspond to the straight line portion of the γ curve 80. Therefore, when the slope of the straight line portion of the γ curve 80 changes, the contrast of the parenchymal organ depicted on the magnetic resonance image changes.

Further, during magnetic resonance imaging, the values of MR signals generated from the blood vessel vasculature are mainly included in range C shown in FIG. 3 . The MR signal values in range C correspond to the shoulder of the γ curve 80. Therefore, when the slope of the shoulder of the γ curve 80 changes, the contrast of the blood vessel vasculature depicted on the magnetic resonance image changes.

Since the MR signal values are different between the blood vessel vasculature and the parenchymal organ, the adjustment regions are also different. In the example shown in FIG. 3, an adjustment region 91 corresponding to the straight line portion of the γ curve 80 is an adjustment region when the region of interest is a real organ. Further, an adjustment region 92 corresponding to the shoulder of the γ curve 80 is an adjustment region when the region of interest is the blood vessel vasculature.

It is assumed that the correspondence between the anatomical type of tissue and the adjustment region 91 is stored in the storage circuit 122 in advance, for example.

The specific function 123e sends the specified adjustment area 91 or adjustment area 92 to the display control function 123f. Hereinafter, when the adjustment area 91 and the adjustment area 92 are not particularly distinguished, they will be referred to as adjustment area 9.

Returning to FIG. 1, the display control function 123f displays various GUIs, magnetic resonance images, various images, etc. on the display 125.

For example, the display control function 123f displays on the display 125 a first operation screen that allows changing the relationship between the MR signal value and the brightness in the adjustment region 9 specified by the specific function 123e.

FIG. 4 is a diagram showing an example of the first operation screen 1251 according to the present embodiment. As shown in FIG. 4, the display control function 123f displays an initial corrected image 70 and a plurality of contrast adjusted images 71a to 71c on the display 125. Hereinafter, when the contrast-adjusted images 71a to 71c are not distinguished, they will simply be referred to as the contrast-adjusted image 71.

The first operation screen 1251 is a screen that allows the operator to change the relationship between the MR signal value and the brightness in the adjustment area 9. More specifically, the first operation screen 1251 is a screen on which the slope or inflection point of the portion of the γ curve 80 included in the adjustment region 9 can be changed. The process performed on the first operation screen 1251 is called contrast adjustment process.

For example, in FIG. 4, it is assumed that blood vessels in the head are designated as the region of interest. Each of the contrast-adjusted images 71a to 71c is a magnetic resonance image in which the shoulder slope and inflection point of the γ curve 80 are different.

Furthermore, the display control function 123f displays graphs 710a to 710c of the adjusted γ curves, superimposed on each of the contrast adjusted images 71a to 71c. The adjusted γ curve graphs 710a to 710c are images representing the γ curves 80a to 80c in each of the contrast adjusted images 71a to 71c. The γ curves 80a to 80c are images in which the slope and inflection point of the γ curve 80 in the adjustment region 92 corresponding to the shoulder of the initially corrected γ curve 80 have been changed. Note that as the slope and inflection point of the γ curve 80 included in the adjustment region 92 change, the overall shape of the γ curve 80 also changes.

The display control function 123f displays adjustment area frames 920a to 920c indicating a range corresponding to the adjustment area frame 920, superimposed on each of the adjusted γ curve graphs 710a to 710c. Hereinafter, when the graphs 710a to 710c of the adjusted γ curves are not distinguished from each other, they will simply be referred to as the graph 710 of the adjusted γ curves. Further, when the adjustment area frames 920a to 920c are not distinguished, they are simply referred to as adjustment area frames 920.

In other words, the contrast adjustment images 71a to 71c in FIG. 4 are preview images representing changes in the magnetic resonance images in which changes in the γ curve 80 in the adjustment region 92 are reflected.

The slope and inflection point of the γ curve 80 change depending on the values of parameters "n" and "k". In the example shown in FIG. 4, the display control function 123f displays the values of parameters "n" and "k" corresponding to each of the contrast-adjusted images 71a-71c in the vicinity of each of the contrast-adjusted images 71a-71c.

The layout of the first operation screen 1251 shown in FIG. 4, the number of contrast-adjusted images 71, the number of adjusted γ curve graphs 710, and the values of parameters "n" and "k" are examples, and are not limited to these. It's not something you can do.

When the operator selects one of the contrast adjustment images 71a to 71c displayed on the first operation screen 1251, the reception function 123c receives the values of parameters "n" and "k" of the selected contrast adjustment image 71. , are accepted as the values of the adjusted parameters "n" and "k".

That is, by selecting any of the contrast adjustment images 71a to 71c on the first operation screen 1251, the operator can change the slope or inflection point of the portion of the γ curve 80 included in the adjustment region 9. You can select the later value.

In addition, after the operator selects one of the contrast adjustment images 71, the display control function 123f adjusts the slope and inflection point of the portion of the γ curve 80 included in the adjustment region 9 in the selected contrast adjustment image 71. The plurality of changed contrast adjustment images 71 are further displayed. The plurality of contrast adjustment images 71 displayed at this point are selected from "contrast adjustment images 71 not selected by the operator" among the plurality of contrast adjustment images 71 displayed on the first operation screen 1251 before the selection operation. is also an image whose values of parameters "n" and "k" are close to "contrast adjustment image 71 selected by the operator". These images are referred to as a plurality of contrast-adjusted images 71 obtained by finely adjusting one contrast-adjusted image 71 selected by the operator.

For example, the display control function 123f displays the contrast adjustment image 71 selected by the operator at the position of the initial correction image 70 in FIG. Further, the display control function 123f selectably displays a plurality of contrast adjustment images 71 in which the contrast of the contrast adjustment image 71 selected by the operator is finely adjusted at the positions of the contrast adjustment images 71a to 71c in FIG. . By repeating the selection operation on the first operation screen 1251 and narrowing down the target, the operator can specify the contrast desired by the operator with high precision.

Furthermore, by changing the size or shape of the adjustment area frame 920 of the adjusted γ-curve graph 710 displayed on the first operation screen 1251, the operator can change the slope of the γ-curve 80 included in the adjustment area 9 or The inflection point can be changed. The operation for changing the size or shape of the adjustment area frame 920 is, for example, a drag-and-drop operation using a mouse, but is not limited to this. Changes to the γ curve 80 by the operator are accepted by the reception function 123c. In this case, the display control function 123f displays the contrast adjustment image 71 on the first operation screen 1251, in which the change of the γ curve 80 accepted by the reception function 123c is reflected.

The operator changes the γ curve 80 in the portion included in the adjustment area 9 by performing a selection operation or drag and drop operation on the first operation screen 1251, thereby changing the parameter “n” that defines the γ curve 80. ” or change the value of “k”.

The display control function 123f also displays on the display 125 a second operation screen that can accept an operation to change the pixel value of the magnetic resonance image. The operation of changing the pixel values of the magnetic resonance image is an operation of correcting the brightness of the entire magnetic resonance image. The brightness of the entire magnetic resonance image is determined by the parameter "t" and the parameter "s" among the parameters defining the γ curve 80. The processing performed on the second operation screen is referred to as adjustment processing of pixel values of the entire magnetic resonance image.

In this embodiment, the second operation screen is displayed after the contrast adjustment in the region of interest by the first operation screen 1251 is completed, but the display order is not limited to this.

FIG. 5 is a diagram showing an example of the second operation screen 1252 according to the present embodiment. As shown in FIG. 5, the display control function 123f displays one contrast-adjusted image 72 and a plurality of pixel value-adjusted images 73a to 73h on the display 125.

The contrast-adjusted image 72 is a magnetic resonance image in which contrast adjustment in the region of interest using the first operation screen 1251 has been completed. In the example shown in FIG. 5, the pixel value adjusted images 73a to 73h display the contrast adjusted image 72 as a reference image before pixel value adjustment.

The pixel value adjusted images 73a to 73h are magnetic resonance images in which the pixel values of the contrast adjusted image 72 have been changed. Further, the display control function 123f displays the values of parameters "t" and "s" corresponding to each of the pixel value adjusted images 73a to 73h in the vicinity of the pixel value adjusted images 73a to 73h. Hereinafter, when the pixel value adjusted images 73a to 73h are not distinguished, they will simply be referred to as the pixel value adjusted image 73.

Further, the layout of the second operation screen 1252, the number of pixel value adjustment images 73, and the values of the parameters "t" and "s" shown in FIG. 5 are examples, and the present invention is not limited to these.

When the operator selects one of the pixel value adjustment images 73 displayed on the second operation screen 1252, the reception function 123c receives the values of the parameters "t" and "s" of the selected pixel value adjustment image 73. , are accepted as the values of the adjusted parameters "t" and "s".

In addition, after the operator selects one of the pixel value adjustment images 73, the display control function 123f controls the value of the parameter "t" or "s" that defines the γ curve 80 in the selected pixel value adjustment image 73. A plurality of pixel value adjustment images 73 whose values have been finely adjusted are further displayed. By repeating the selection process and narrowing down the target, the operator can specify the pixel value desired by the operator with high precision.

The display control function 123f also displays on the display 125 a third operation screen that can accept operations for individually changing parameters that define the brightness of the magnetic resonance image.

The third operation screen displays, for example, the parameters "t", "n", "k", and "s" of the magnetic resonance image after the brightness has been adjusted on the first operation screen 1251 and the second operation screen 1252. This screen allows you to fine-tune the values individually. The process performed on the third operation screen is called fine adjustment process.

FIG. 6 is a diagram showing an example of the third operation screen 1253 according to the present embodiment. As shown in FIG. 6, the display control function 123f displays a pre-fine adjustment magnetic resonance image 74 and a post-fine adjustment magnetic resonance image 75 on the display 125.

The pre-fine adjustment magnetic resonance image 74 is a magnetic resonance image before the values of the parameters “t”, “n”, “k”, and “s” are finely adjusted on the third operation screen 1253. The pre-fine adjustment magnetic resonance image 74 is, for example, a pixel value adjusted image 73 whose pixel values have been adjusted on the second operation screen 1252.

Further, the display control function 123f displays the gradation information display area 60. The gradation information display area 60 includes an operation section 62 that can adjust the values of the parameters "t", "n", "k", and "s"; A γ curve 80 defined by the value of s'' is displayed.

The operation unit 62 is, for example, a parameter bar that allows the operator to change the values of parameters "t", "n", "k", and "s" by dragging and dropping, but is not limited to this. . When the operator changes the values of parameters "t", "n", "k", and "s", the display control function 123f displays a γ curve 80 finely adjusted according to the changed values of each parameter, The finely adjusted magnetic resonance image 75 is displayed.

The range in which the operator can change the values of the parameters "t", "n", "k", and "s" on the third operation screen 1253 may be limited to a predetermined amount of change or less. For example, the numerical ranges of parameters “t”, “n”, “k”, and “s” that can be changed by the operator on the third operation screen 1253 are different from those on the first operation screen 1251 or the second operation screen 1252. It shall be narrower than the width of the numerical value that can be changed in .

Returning to FIG. 1, the image correction function 123g corrects the brightness of the magnetic resonance image based on the γ curve 80. For example, the image correction function 123g generates the initial correction image 70 by correcting the brightness of the original image based on the γ curve 80 generated by the gradation information generation function 123d, that is, the gradation information after initial correction. do.

The image correction function 123g also generates a plurality of contrast adjustment images 71 in which the values of parameters "n" and "k" of the initial correction image 70 are changed.

The image correction function 123g also generates a contrast-adjusted image 72 by correcting the contrast of the initial correction image 70 based on the γ curve 80 changed by the operator on the first operation screen 1251.

In addition, the image correction function 123g corrects the pixel values of the entire contrast-adjusted image 72 based on the γ curve 80 changed by the operator on the second operation screen 1252. generate.

The image correction function 123g also corrects the pre-fine adjustment magnetic resonance image 74 based on the parameters “t”, “n”, “k”, and “s” changed by the operator on the third operation screen 1253. By doing so, a finely adjusted magnetic resonance image 75 is generated.

The image correction function 123g sends the generated initial correction image 70, contrast-adjusted image 71, contrast-adjusted image 72, and finely adjusted magnetic resonance image 75 to the display control function 123f.

The image correction function 123g also stores the generated finely adjusted magnetic resonance image 75 in the storage circuit 122 as a diagnostic image used for diagnosis. Further, the image correction function 123g may also store the initial corrected image 70, the contrast-adjusted image 71, and the contrast-adjusted image 72 in the storage circuit 122.

Next, the flow of brightness adjustment processing executed by the MRI apparatus 100 configured as above will be described.

FIG. 7 is a flowchart showing an example of the flow of brightness adjustment processing according to this embodiment.

First, the collection function 123a collects MR data by executing various pulse sequences (S1). Furthermore, the collection function 123a generates k-space data from the collected MR data.

The reconstruction function 123b then generates a magnetic resonance image from the k-space data (S2). The magnetic resonance image generated in the process of S2 is an original image. The processing of S1 and S2 may be combined into magnetic resonance image imaging processing.

Next, the gradation information generation function 123d generates a γ curve 80 based on the initial values of the parameters “t”, “n”, “k”, and “s” and the maximum value of the MR signal value in the original image. (S3).

Next, the reception function 123c receives the designation of the region of interest by the operator (S4). For example, the reception function 123c accepts a range specified by the operator on the magnetic resonance image displayed on the display 125 as a region of interest. The magnetic resonance image displayed for specifying the region of interest may be, for example, the original image, or may be another magnetic resonance image having the same imaging range as the original image, such as a locator image.

Alternatively, the reception function 123c may input the name of the organ or the like of the region of interest from the GUI displayed on the display 125. Further, the reception function 123c may select from the GUI displayed on the display 125 whether the region of interest belongs to the "vascular vasculature" or the "real organ".

Note that the method for specifying the region of interest is not limited to input by the operator. For example, a configuration may be adopted in which the specifying function 123e specifies the region of interest based on imaging conditions or the like.

Next, the specifying function 123e specifies the adjustment region 9 in the γ curve 80 according to the specified region of interest (S5). The specific function 123e sends the specified adjustment area 9 to the display control function 123f.

Then, the display control function 123f displays on the display 125 a first operation screen 1251 that allows changing the relationship between the MR signal value and the brightness in the adjustment region 9 specified by the specific function 123e (S6).

Next, the reception function 123c determines whether the operator has received an operation for selecting any one of the plurality of contrast adjustment images 71 displayed on the first operation screen 1251 (S7).

If the reception function 123c determines that the selection of the contrast adjustment image 71 has not been accepted (S7 "No"), the reception function 123c determines whether or not an operation to change the size or shape of the adjustment area frame 920 by the operator has been accepted. (S8).

If it is determined that the operator's operation to change the size or shape of the adjustment area frame 920 is not accepted (S8 "No"), the process returns to S7.

Further, if it is determined that an operation to change the size or shape of the adjustment area frame 920 by the operator has been received (S8 "Yes"), the reception function 123c accepts an operation to change the size or shape of the adjustment area frame 920. The slope or inflection point of the γ curve 80 included in the changed adjustment region 9 is accepted. The reception function 123c sends the changed slope or inflection point of the γ curve 80 to the image correction function 123g.

The image correction function 123g generates a contrast-adjusted image 72 by correcting the contrast of the initial correction image 70 based on the γ curve 80 changed by the operator on the first operation screen 1251 (S9).

The display control function 123f displays the contrast-adjusted image 72 generated by the image correction function 123g on the first operation screen 1251 (S10). For example, the display control function 123f may replace the contrast-adjusted image 71 displayed together with the adjustment area frame 920 changed by the operator with the contrast-adjusted image 72.

Further, when the reception function 123c determines that the selection of the contrast adjustment image 71 has been accepted (S7 "Yes"), the reception function 123c determines whether or not the contrast adjustment process in the region of interest specified in S4 has been completed (S11). For example, the reception function 123c determines that the contrast adjustment process is completed when the operator performs an operation to complete the contrast adjustment process in the region of interest. Alternatively, the reception function 123c may determine that the contrast adjustment process is completed when the selection operation of the contrast adjustment image 71 is repeated a predetermined number of times.

Then, if the receiving function 123c determines that the contrast adjustment process in the region of interest specified in S4 is not completed (S11 "No"), the contrast of the contrast adjustment image 71 selected in S7 is finely adjusted. A plurality of contrast adjustment images 71 are displayed in a selectable manner on the first operation screen 1251 (S12).

Then, the process returns to S7, and the processes of S7 to S12 are repeated until the contrast adjustment process in the region of interest specified in S4 is completed.

Then, when the reception function 123c determines that the contrast adjustment process in the region of interest specified in S4 is completed (S11 "Yes"), the reception function 123c stores the changed values of each parameter "n" and "k" in the storage circuit 122. In this case, the reception function 123c determines whether another region of interest has been specified (S13).

A single magnetic resonance image may include multiple regions of interest. For example, when the operator inputs the completion of the contrast adjustment process for the region of interest, the display control function 123f may display a GUI that can accept the designation of another region of interest. Although this flowchart describes an example in which the operator specifies individual regions of interest, the display control function 123f may determine whether a plurality of regions of interest exist based on imaging conditions or the like.

Further, when receiving the designation of another region of interest, the receiving function 123c determines that another region of interest has been designated (S13 "Yes"). In this case, the process returns to S5, and contrast adjustment processes S5 to S13 in other regions of interest are executed.

Further, if the reception function 123c determines that no other region of interest is specified (S13 "No"), the display control function 123f displays the second operation screen 1252 (S14).

Then, the reception function 123c determines whether a selection of any of the pixel value adjustment images 73 displayed on the second operation screen 1252 has been received (S15).

If the reception function 123c determines that the selection of any of the pixel value adjustment images 73 is not accepted (S15 “No”), the display control function 123f continues displaying the second operation screen 1252.

Further, if the reception function 123c determines that the selection of the pixel value adjustment image 73 has not been accepted (S15 "No"), the reception function 123c determines whether or not the pixel value adjustment process for the entire magnetic resonance image is completed (S16 ).

For example, the reception function 123c determines that the pixel value adjustment process has been completed when the operator performs an operation to complete the pixel value adjustment process for the entire magnetic resonance image. Alternatively, the reception function 123c may determine that the pixel value adjustment process is completed when the selection operation of the pixel value adjustment image 73 is repeated a predetermined number of times.

Then, if the reception function 123c determines that the pixel value adjustment processing of the entire magnetic resonance image is not completed (S16 "No"), the pixel values of the pixel value adjustment image 73 selected in S15 are finely adjusted. The plurality of pixel value adjustment images 73 are displayed in a selectable manner on the second operation screen 1252 (S17).

Then, the process returns to S15, and the processes of S15 to S17 are repeated until the pixel value adjustment process for the entire magnetic resonance image is completed.

If the reception function 123c determines that the pixel value adjustment process for the entire magnetic resonance image is completed (S16 "Yes"), the changed values of the parameters "t" and "s" are stored in the storage circuit 122. do. Further, in this case, the display control function 123f displays the third operation screen 1253 on the display 125 (S18).

Then, the reception function 123c determines whether an operation for changing one or more values of the parameters "t", "n", "k", and "s" is received on the third operation screen 1253. (S19).

If the reception function 123c determines that the operation to change the values of the parameters “t”, “n”, “k”, and “s” is not accepted (S19 “No”), the reception function 123c displays the information on the third operation screen 1253. Continue displaying.

In addition, if the reception function 123c determines that an operation to change the values of the parameters "t", "n", "k", and "s" has been accepted (S19 "Yes"), the value of each parameter after the change is determined. is stored in the memory circuit 122.

In addition, in this case, the image correction function 123g corrects the pre-fine adjustment magnetic resonance image 74 based on the changed parameters "t", "n", "k", and "s". A magnetic resonance image 75 is generated (S20).

Then, the display control function 123f displays the finely adjusted magnetic resonance image 75 on the third operation screen 1253 (S21). Further, the display control function 123f displays the γ curve 80 finely adjusted according to the changed values of each parameter on the third operation screen 1253.

Next, the reception function 123c determines whether the fine adjustment process for the values of parameters "t", "n", "k", and "s" has been completed (S22). For example, the reception function 123c determines that the fine adjustment process is completed when the operator performs an operation to complete the fine adjustment process.

When the reception function 123c determines that the fine adjustment process is not completed (S22 "No"), the reception function 123c returns to the process of S19.

Further, if the reception function 123c determines that the fine adjustment process is completed (S22 "Yes"), the display control function 123f and the image correction function 123g update the latest parameters finely adjusted on the third operation screen 1253. The finely adjusted magnetic resonance image 75 based on the values of "t", "n", "k", and "s" is displayed on the display 125 as a diagnostic image used for diagnosis (S23). At this point, the processing of this flowchart ends.

In this flowchart, it is assumed that the process for determining whether or not the designation of another region of interest has been accepted is executed after the contrast adjustment process for the region of interest specified in S4 is completed. is not limited to this. For example, after the parameter fine adjustment process on the third operation screen 1253 is completed, the process of determining whether the designation of another region of interest has been accepted may be executed.

Furthermore, the contrast adjustment process in the same region of interest may be executed multiple times. For example, after the pixel value adjustment process for the entire magnetic resonance image is completed, the contrast adjustment process in the region of interest may be performed again.

In this manner, the MRI apparatus 100 of the present embodiment specifies the adjustment region 9 that accepts adjustment by the operator in the γ curve 80 according to the region of interest on the magnetic resonance image taken of the subject, and The change of the γ curve 80 by the operator is accepted. With this configuration, according to the MRI apparatus 100 of the present embodiment, the operator can easily grasp and change the part of the γ curve 80 that defines the brightness of the entire magnetic resonance image according to the region of interest. can be operated. Therefore, according to the MRI apparatus 100 of this embodiment, it is possible for the operator to easily adjust the contrast according to the region of interest in the magnetic resonance image.

Furthermore, the MRI apparatus 100 of this embodiment specifies different adjustment regions 9 depending on the anatomical type of tissue depicted in the region of interest. Therefore, according to the MRI apparatus 100 of this embodiment, it is possible to adjust the correspondence between the MR signal value and the brightness within the range of values that the MR signal generated from the tissue depicted in the region of interest can take.

Furthermore, the MRI apparatus 100 of the present embodiment displays a contrast adjustment image 71 on the first operation screen 1251 in which a change in the slope or inflection point of the γ curve 80 in the adjustment region is reflected. Therefore, according to the MRI apparatus 100 of this embodiment, the operator can execute the contrast adjustment process while checking the contrast after adjustment.

Furthermore, the MRI apparatus 100 of the present embodiment displays on the display 125 a second operation screen 1252 that can accept an operation to change the entire pixel value of the contrast-adjusted image 72 in which the change in the γ curve 80 is reflected. . Therefore, according to the MRI apparatus 100 of this embodiment, the operator can adjust the brightness of the entire magnetic resonance image based on the contrast adjustment result of the region of interest.

Note that in this embodiment, the γ curve has been described as an example of gradation information, but the gradation information is not limited to this. For example, the gradation information may be represented by various tone curves such as spline curves.

Further, the operator may adjust the brightness using only one or two of the first operation screen 1251, the second operation screen 1252, and the third operation screen 1253. Further, the MRI apparatus 100 does not necessarily have all the functions of the first operation screen 1251, the second operation screen 1252, and the third operation screen 1253. For example, the MRI apparatus 100 may adopt a configuration that does not have the function of fine adjustment processing using the third operation screen 1253.

Furthermore, in this embodiment, the reconstruction function 123b, the gradation information generation function 123d, the specific function 123e, and the image correction function 123g have been described as separate functions, but the gradation information generation function 123d, the specific function 123e, and Part or all of the image correction function 123g may be included in the reconstruction function 123b.

Furthermore, the range in which the operator can change the slope or inflection point of the γ curve 80 included in the adjustment area 9 on the first operation screen 1251 described with reference to FIG. 4 and the like may be defined in advance.

For example, depending on the degree of inclination of the γ curve 80, the region of interest or the entire magnetic resonance image may be completely white or completely black. Therefore, the range in which the values of the parameters "n" and "k" can be changed by the operator is within the range of the values of the parameters "n" and "k" that allow organs, etc. to be visualized on the magnetic resonance image. may be specified.

Further, depending on the imaging sequence, the contrast of the magnetic resonance image or the pixel value of the entire magnetic resonance image may change depending on the sex or age of the subject P. For example, the display control function 123f may limit the changeable range of the size or shape of the adjustment region frame 920 based on the imaging conditions or patient information regarding the subject P. Alternatively, the gradation information generation function 123d may adjust the values of the parameters "t", "n", "k", and "s" based on the imaging conditions or patient information regarding the subject P. For example, in MRA (Magnetic Resonance Angiography), when the subject P is elderly, the contrast of the magnetic resonance image tends to be low. Therefore, when the subject P is elderly, the gradation information generation function 123d may adjust the values of each parameter so as to increase the pixel value of the entire magnetic resonance image.

In addition, the gradation information generation function 123d estimates a signal-to-noise ratio (SNR) based on information such as the coil used for imaging and the magnetic field strength of the static magnetic field magnet 101, and estimates the signal-to-noise ratio (SNR). Based on the ratio, an appropriate adjustment range of the slope or inflection point of the γ curve 80 may be calculated.

Note that the conditions defining the range in which the values of the parameters "n" and "k" can be changed by the operator are not limited to these conditions. Furthermore, the range in which the slope or inflection point of the γ curve 80 can be changed may be stored in the storage circuit 122 as, for example, upper and lower limit values of the values of the parameters "n" and "k". Furthermore, the changeable range of the parameters "t" and "s" may be defined according to various conditions.

(Second embodiment)
In the first embodiment described above, a case has been described in which the brightness of one magnetic resonance image is individually adjusted. In this second embodiment, an example will be described in which the adjustment results of parameters "t", "n", "k", and "s" regarding one magnetic resonance image are also applied to brightness adjustment of other magnetic resonance images. explain.

The configuration of the MRI apparatus 100 according to this embodiment is the same as that of the first embodiment.

In this embodiment, the display control function 123f adjusts the values of the parameters "t", "n", "k", and "s" adjusted by the previous brightness adjustment process to the brightness of the newly captured magnetic resonance image. A fourth selection screen is displayed on the display 125, allowing the operator to select whether or not to apply the adjustment.

FIG. 8 is a diagram illustrating an example of options that can be selected by the operator according to the present embodiment. For example, in FIG. 8, it is assumed that "imaging routine xx" was executed in the previous imaging. The "imaging routine xx" is an example of a set of imaging processing that combines imaging of a plurality of magnetic resonance images. In the MRI apparatus 100 of this embodiment, it is assumed that a plurality of sets of definition information of combined imaging processes are stored in the storage circuit 122 for each imaging site or imaging condition. Further, individual imaging processing included in one set of imaging processing is called a protocol.

The set of imaging processing and the values of parameters "t", "n", "k", and "s" corresponding to the set may be registered in advance in the storage circuit 122 by the vendor of the MRI apparatus 100, for example. . Further, a doctor, a technician, or the like who uses the MRI apparatus 100 sets a set of imaging processing and values of parameters "t", "n", "k", and "s" corresponding to the set, and stores them in the storage circuit 122. It may also be something to register.

Further, in this embodiment, it is assumed that the values of parameters "t", "n", "k", and "s" are defined and stored in the storage circuit 122 for each set of imaging processing.

In the example shown in FIG. 8, the brightness adjustment process for the previously captured magnetic resonance image is executed, and the parameters "t", "n", "k", and "s" for "imaging routine xx" are It is assumed that the adjustment has been completed by the operator. Note that the method for adjusting the parameters "t", "n", "k", and "s" is the same as in the first embodiment.

In this case, it is assumed that the operator can select any one of options 1 to 3 on the fourth selection screen for the magnetic resonance image captured in the current imaging.

Option 1 is to adjust the brightness of the magnetic resonance image by using the previously adjusted parameters "t", "n", "k", and "s" as they are.

Option 2 is to execute the brightness adjustment process based on the values of the parameters "t", "n", "k", "s" before adjustment, and to create new parameters "t", "n", "k", "s". The purpose is to determine the value of "s". The values of the parameters "t", "n", "k", and "s" before adjustment are, for example, values stored in the storage circuit 122 as initial values. When the operator selects option 2, the same brightness adjustment process as in the first embodiment is executed.

Option 3 is to determine the parameters by further performing brightness adjustment from the state of the previously adjusted parameters "t", "n", "k", and "s". In this case, on the first operation screen 1251, a magnetic resonance image whose brightness has been adjusted based on the previously adjusted parameters "t", "n", "k", and "s" is displayed as the initial corrected image 70. be done.

No matter which of options 1 to 3 is selected by the operator, the values of the parameters “t”, “n”, “k”, and “s” used as a result of the selection are stored in the storage circuit 122. shall be. For example, if option 2 or 3 is selected, the values of the parameters “t”, “n”, “k”, and “s” that were previously adjusted will be changed and stored in the storage circuit 122. do. Alternatively, the changed values of parameters "t", "n", "k", and "s" may be individually stored each time adjustment is made.

When adjusting the brightness of the magnetic resonance image in the next imaging, do you want to use the values of the parameters “t”, “n”, “k”, and “s” that were used this time, or set new values from the initial values? , it becomes possible to select whether to execute the brightness adjustment process based on the values of the parameters "t", "n", "k", and "s" used this time.

Although the "imaging routine xx" includes a plurality of imaging processes, only one imaging process may be defined as the "imaging routine xx".

Further, in FIG. 8, a case has been described in which the same "imaging routine xx" is executed multiple times, but the parameters "t", "n", "k" for a certain combination of imaging processing or one imaging processing are , "s" may be applied to other different combinations of imaging processing or to other different single imaging processing. Application conditions include, for example, "regions of interest are common," "imaging regions are common," "imaging protocols included in one set of imaging processing are the same," and "subjects P are the same." ”, “The imaging sequence is common”, etc.

It is assumed that the conditions for applying the values of the parameters "t", "n", "k", and "s" after brightness adjustment to other imaging processing can be selected by the operator.

For example, when the reception function 123c receives settings for application conditions from the operator, the gradation information generation function 123d selects a setting associated with an imaging process that satisfies the application conditions from among the imaging processes stored in the storage circuit 122. The parameter values may be changed to the values of the parameters "t", "n", "k", and "s" after brightness adjustment. Alternatively, when the imaging process that satisfies the application conditions is executed, the display control function 123f displays the fourth selection screen and displays the parameters "t", "n", "k", "s" after brightness adjustment. The operator may be able to select whether or not to apply the value of ``.

Furthermore, parameters "t", "n", "k", and "s" associated with individual imaging processes included in one set of imaging processes may be different. In such a case, in the present embodiment, the gradation information generation function 123d uses the adjustment results of parameters "t", "n", "k", and "s" regarding one magnetic resonance image to generate other magnetic resonance images. Also applies to brightness adjustment.

FIG. 9 is a diagram illustrating an example of reflection of parameter adjustment results for different protocols according to the present embodiment. The "imaging routine yy" shown in FIG. 9 includes (1) collection of maps for shimming, (2) imaging of T1-weighted images, (3) imaging of T2-weighted images, and (4) imaging of MRA3D. Contains 4 types of protocols. (1) Collection of the map for shimming is preparation for the imaging processing after (2), so no magnetic resonance image for diagnosis is generated.

In FIG. 9, it is assumed that the values of parameters "t", "n", "k", and "s" are changed in order to adjust the brightness of the magnetic resonance image captured in the process (2). In this case, the gradation information generation function 123d generates parameters "t", "n", "k", "s" used in the brightness adjustment of the magnetic resonance images captured in the processes (3) and (4). The value of is changed at the same rate as the amount of change in the values of the parameters "t", "n", "k", and "s" adjusted for brightness adjustment of the magnetic resonance image captured in the process (2). Update. For example, in order to adjust the brightness of the magnetic resonance images captured in the process (2), the value of the parameter "t" is doubled, so the magnetic resonance images captured in the processes (3) and (4) The value of the parameter "t" used in the brightness adjustment of the resonance image is also doubled.

Also, if all imaging processing in "imaging routine yy" has been completed at the time the values of the processing parameters "t", "n", "k", and "s" in (2) are changed. The brightness of the magnetic resonance images captured in (3) and (4) is adjusted by the updated value by the image correction function 123g. The display control function 123f displays the image whose brightness has been adjusted with the updated value on the display 125 as the imaging results of (3) and (4).

In this case, before the values of the processing parameters "t", "n", "k", and "s" in (2) are changed, they have already been generated based on the parameter values before adjustment ( The magnetic resonance images 3) and (4) are stored in the storage circuit 122, but are not initially displayed on the display 125.

Also, if all imaging processing in "imaging routine yy" has not been completed at the time the values of the processing parameters "t", "n", "k", and "s" in (2) are changed. is initially generated with the adjustment of the values of the processing parameters "t", "n", "k", and "s" reflected in (2) for the protocol during or before imaging. shall be taken as a thing.

In this way, according to the MRI apparatus 100 of the present embodiment, the adjustment results of the parameters "t", "n", "k", and "s" regarding one magnetic resonance image are used to adjust the brightness of another magnetic resonance image. By applying the present invention to the present invention, the operator does not have to perform parameter adjustment work every time an image is taken, so that the work time can be shortened.

(Modified example)
In the first and second embodiments described above, the MRI apparatus 100 is used as an example of an image processing apparatus, but the image processing apparatus may be a different apparatus from the MRI apparatus 100.

FIG. 10 is a diagram showing an example of the overall configuration of the medical information system S according to this modification. As shown in FIG. 10, the medical information system S includes an MRI apparatus 1100 and an image processing apparatus 200. The MRI apparatus 1100 and the image processing apparatus 200 are connected via a network 300 such as an in-hospital LAN (Local Area Network).

Further, as in the first embodiment, the MRI apparatus 1100 includes a static magnetic field magnet 101, a gradient magnetic field coil 102, a gradient magnetic field power source 103, a bed 104, a bed control circuit 105, a transmitter coil 106, and a transmitter. It includes a circuit 107, a receiving coil 108, a receiving circuit 109, a sequence control circuit 110, a computer system 120, and a gantry 150.

The image processing device 200 is, for example, a PC (Personal Computer) or a server device. The image processing device 200 includes a network interface 221, a storage circuit 222, a processing circuit 223, an input interface 224, and a display 225. The display 225 is an example of a display unit according to this embodiment.

The processing circuit 223 of the image processing device 200 includes an acquisition function 223a, a reception function 223b, a gradation information generation function 223c, a specific function 223d, a display control function 223e, and an image correction function 223f. The acquisition function 223a is an example of an acquisition unit. The reception function 223b is an example of a reception unit. The gradation information generation function 223c is an example of a gradation information generation section. The specific function 223d is an example of a specific part. The display control function 223e is an example of a display control section. The image correction function 223f is an example of an image correction section.

The processing functions of the acquisition function 223a, the reception function 223b, the gradation information generation function 223c, the specific function 223d, the display control function 223e, and the image correction function 223f, which are the constituent elements of the processing circuit 223, are executed by a program executable by a computer. It is stored in the storage circuit 222 in the form The processing circuit 223 reads each program from the storage circuit 222 and executes each read program, thereby realizing a function corresponding to each program. In other words, the processing circuit 223 in a state where each program has been read has each function shown in the processing circuit 223 of FIG. Further, the processing circuit 223 may be configured by combining a plurality of independent processors, and each processor may implement each processing function by executing each program.

The acquisition function 223a acquires a magnetic resonance image from the MRI apparatus 1100. The acquisition function 223a stores the acquired magnetic resonance image in the storage circuit 222.

In addition, each of the reception function 223b, gradation information generation function 223c, specific function 223d, display control function 223e, and image correction function 223f of the first embodiment includes the collection function 123a, the reconstruction function 123b, the reception function 123c, It has the same functions as a gradation information generation function 123d, a specific function 123e, a display control function 123f, and an image correction function 123g.

According to at least one embodiment described above, it is possible for an operator to easily adjust contrast according to a region of interest in a magnetic resonance image.

Although several embodiments of the invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and changes can be made without departing from the gist of the invention. These embodiments and their modifications are included within the scope and gist of the invention as well as within the scope of the invention described in the claims and its equivalents.

9, 91, 92 Adjustment area 70 Initial correction image 71, 71a to 71c Contrast adjustment image 72 Contrast adjusted image 73, 73a Pixel value adjustment image 74 Magnetic resonance image before fine adjustment 75 Magnetic resonance image after fine adjustment 80, 80a to 80c γ curve 100, 1100 MRI apparatus 122 Memory circuit 123a Acquisition function 123b Reconfiguration function 123c Reception function 123d Gradation information generation function 123e Specific function 123f Display control function 123g Image correction function 123 Processing circuit 124 Input interface 125 Display 200 Image processing device 221 Network interface 222 Storage circuit 223a Acquisition function 223b Reception function 223c Gradation information generation function 223d Specific function 223e Display control function 223f Image correction function 223 Processing circuit 224 Input interface 225 Display 710, 710a to 710c Adjusted γ curve graph 920, 920a ~920c Adjustment area frame 1251 First operation screen 1252 Second operation screen 1253 Third operation screen P Subject S Medical information system

Claims (8)

a specifying unit that specifies a region that accepts adjustment by an operator in gradation information representing a relationship between an MR signal value and brightness according to a region of interest on a magnetic resonance image taken of the subject;
a reception unit that receives a change in the relationship between the MR signal value and the brightness in the area specified by the identification unit;
A first operation screen that accepts contrast adjustment processing in the magnetic resonance image corresponding to the change , a second operation screen that accepts adjustment processing of pixel values of the entire magnetic resonance image , and a selectable selection screen indicating whether or not to apply the value of the parameter defining the brightness of the adjusted magnetic resonance image to the brightness adjustment of the newly captured magnetic resonance image; and displaying on the display unit. a display control section;
An image processing device comprising: The gradation information is a characteristic curve representing the relationship between the MR signal value and the luminance,
The region is a range of the characteristic curve in which the operator can change the characteristic curve.
The image processing device according to claim 1. The first operation screen is an operation screen that allows changing the slope or inflection point of a portion of the characteristic curve included in the region,
The selection screen is an imaging process that combines imaging of a plurality of magnetic resonance images,
The imaging processing includes the following: a common region of interest, a common imaging site, the same imaging protocol, the same subject, and a common imaging sequence. including,
The image processing device according to claim 2. The specifying unit specifies the different regions depending on the anatomical type of the tissue depicted in the region of interest.
The image processing device according to any one of claims 1 to 3. The anatomical type is classified into vascular vasculature and parenchymal organs.
The image processing device according to claim 4. The reception unit accepts a change in the slope or inflection point of the characteristic curve in the region,
The display control unit displays the magnetic resonance image in which the change in the characteristic curve received by the reception unit is reflected on a display unit.
The image processing device according to claim 2. The display control unit displays the first operation screen and the second operation screen on the display unit.
The image processing device according to claim 6. The MR signal value is the maximum value of MR signal values in the magnetic resonance image,
The image processing device according to claim 2.

Images