Sugimori, 2018 - Google Patents
Classification of computed tomography images in different slice positions using deep learningSugimori, 2018
View PDF- Document ID
- 2122126401976763968
- Author
- Sugimori H
- Publication year
- Publication venue
- Journal of healthcare engineering
External Links
Snippet
This study aimed at elucidating the relationship between the number of computed tomography (CT) images, including data concerning the accuracy of models and contrast enhancement for classifying the images. We enrolled 1539 patients who underwent contrast …
- 238000002591 computed tomography 0 title abstract description 37
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
- G06F19/321—Management of medical image data, e.g. communication or archiving systems such as picture archiving and communication systems [PACS] or related medical protocols such as digital imaging and communications in medicine protocol [DICOM]; Editing of medical image data, e.g. adding diagnosis information
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
- G06F19/322—Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10084—Hybrid tomography; Concurrent acquisition with multiple different tomographic modalities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/22—Health care, e.g. hospitals; Social work
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Sugimori | Classification of computed tomography images in different slice positions using deep learning | |
Torrado-Carvajal et al. | Dixon-VIBE deep learning (DIVIDE) pseudo-CT synthesis for pelvis PET/MR attenuation correction | |
Dangi et al. | A distance map regularized CNN for cardiac cine MR image segmentation | |
Bernard et al. | Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved? | |
Andriole et al. | Optimizing analysis, visualization, and navigation of large image data sets: one 5000-section CT scan can ruin your whole day | |
Arimura et al. | Computerized detection of intracranial aneurysms for three‐dimensional MR angiography: Feature extraction of small protrusions based on a shape‐based difference image technique | |
Oghli et al. | Automatic fetal biometry prediction using a novel deep convolutional network architecture | |
Koshino et al. | Narrative review of generative adversarial networks in medical and molecular imaging | |
Wang et al. | Semi-supervised mp-MRI data synthesis with StitchLayer and auxiliary distance maximization | |
Shen et al. | Breast mass detection from the digitized X-ray mammograms based on the combination of deep active learning and self-paced learning | |
Rubin et al. | Biomedical imaging informatics | |
Ashkani Chenarlogh et al. | Fast and accurate U-net model for fetal ultrasound image segmentation | |
Amirrajab et al. | Label-informed cardiac magnetic resonance image synthesis through conditional generative adversarial networks | |
CN113506310A (en) | Medical image processing method and device, electronic equipment and storage medium | |
Fashandi et al. | An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U‐nets | |
Woo et al. | A spatio-temporal atlas and statistical model of the tongue during speech from cine-MRI | |
Goyal et al. | Skin lesion boundary segmentation with fully automated deep extreme cut methods | |
Gaweł et al. | Automatic spine tissue segmentation from MRI data based on cascade of boosted classifiers and active appearance model | |
Tanner et al. | Quantitative evaluation of free‐form deformation registration for dynamic contrast‐enhanced MR mammography | |
Gheorghiță et al. | Improving robustness of automatic cardiac function quantification from cine magnetic resonance imaging using synthetic image data | |
Anand et al. | Automated classification of intravenous contrast enhancement phase of ct scans using residual networks | |
Ning et al. | DRAN: Deep recurrent adversarial network for automated pancreassegmentation | |
Zreik et al. | Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis | |
Somasundaram et al. | Fetal brain extraction from magnetic resonance image (MRI) of human fetus | |
US20240078089A1 (en) | System and method with medical data computing |