WO2022215530A1 - 医用画像装置、医用画像方法、及び医用画像プログラム - Google Patents

医用画像装置、医用画像方法、及び医用画像プログラム Download PDF

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Publication number
WO2022215530A1
WO2022215530A1 PCT/JP2022/013693 JP2022013693W WO2022215530A1 WO 2022215530 A1 WO2022215530 A1 WO 2022215530A1 JP 2022013693 W JP2022013693 W JP 2022013693W WO 2022215530 A1 WO2022215530 A1 WO 2022215530A1
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WIPO (PCT)
Prior art keywords
interest
region
regions
lesion
medical image
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Ceased
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PCT/JP2022/013693
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English (en)
French (fr)
Japanese (ja)
Inventor
晶路 一ノ瀬
佳児 中村
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Fujifilm Corp
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Fujifilm Corp
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Priority to EP22784515.3A priority Critical patent/EP4321100A4/en
Priority to JP2023512928A priority patent/JPWO2022215530A1/ja
Publication of WO2022215530A1 publication Critical patent/WO2022215530A1/ja
Priority to US18/479,817 priority patent/US20240029252A1/en
Anticipated expiration legal-status Critical
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/46—Arrangements for interfacing with the operator or the patient
    • A61B6/461—Displaying means of special interest
    • A61B6/463—Displaying means of special interest characterised by displaying multiple images or images and diagnostic data on one display
    • G—PHYSICS
    • G06—COMPUTING OR 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
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5217—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data extracting a diagnostic or physiological parameter from medical diagnostic data
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03—Computed tomography [CT]
    • A61B6/032—Transmission computed tomography [CT]
    • G—PHYSICS
    • G06—COMPUTING OR 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
    • G06T2207/30096—Tumor; Lesion
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/03—Recognition of patterns in medical or anatomical images

Definitions

  • the processor when the number of regions of interest having the same attribute as the attribute of the selected region of interest is equal to or greater than a threshold, the processor provides information about the region of interest having an attribute different from the attribute of the selected region of interest. You may perform control to display.
  • control to further display information indicating that the attributes are different may be performed.
  • the medical image program of the present disclosure obtains a medical image, information representing a plurality of regions of interest included in the medical image, and attributes of each of the plurality of regions of interest, and determines at least one region of interest among the plurality of regions of interest. It is for causing a processor included in the medical imaging apparatus to perform a process of controlling the display of information about regions of interest other than the selected region of interest based on the attributes of the selected region of interest.
  • the medical image program of the present disclosure obtains a medical image, information representing a plurality of regions of interest included in the medical image, and attributes of each of the plurality of regions of interest, and determines at least one region of interest among the plurality of regions of interest. This is for causing a processor included in the medical imaging apparatus to execute a process of selecting and generating a finding sentence of a region of interest having the same attribute as the selected region of interest.
  • FIG. 1 is a block diagram showing a schematic configuration of a medical information system
  • FIG. 1 is a block diagram showing an example of the hardware configuration of a medical imaging apparatus
  • FIG. 1 is a block diagram showing an example of a functional configuration of a medical imaging apparatus according to first and second embodiments
  • FIG. It is a figure for demonstrating the process which extracts a lesion.
  • FIG. 10 is a diagram for explaining processing for deriving the name of a lesion; It is a figure which shows an example of the screen by which the lesion was highlighted.
  • 6 is a flowchart showing an example of lesion display processing according to the first embodiment;
  • FIG. 10 is a flowchart showing an example of lesion display processing according to the first embodiment
  • FIG. 1 is a block diagram showing an example of the hardware configuration of a medical imaging apparatus
  • FIG. 1 is a block diagram showing an example of a functional configuration of a medical imaging apparatus according to first and second embodiments
  • FIG. It is a figure for demonstrating the process
  • the medical information system 1 is a system for taking images of a diagnostic target region of a subject and storing the medical images acquired by the taking, based on an examination order from a doctor of a clinical department using a known ordering system.
  • the medical information system 1 is a system for interpretation of medical images and creation of interpretation reports by interpretation doctors, and for viewing interpretation reports and detailed observations of medical images to be interpreted by doctors of the department that requested the diagnosis. be.
  • the image server 5 incorporates a software program that provides a general-purpose computer with the functions of a database management system (DBMS).
  • DBMS database management system
  • the incidental information includes, for example, an image ID (identification) for identifying individual medical images, a patient ID for identifying a patient who is a subject, an examination ID for identifying examination content, and an ID assigned to each medical image. It includes information such as a unique ID (UID: unique identification) that is assigned to the user.
  • the additional information includes the examination date when the medical image was generated, the examination time, the type of imaging device used in the examination for obtaining the medical image, patient information (for example, the patient's name, age, gender, etc.).
  • the interpretation report DB 8 stores, for example, an image ID for identifying a medical image to be interpreted, an interpreting doctor ID for identifying an image diagnostician who performed the interpretation, a lesion name, lesion position information, findings, and confidence levels of findings. An interpretation report in which information such as is recorded is registered.
  • the interpretation WS 3 requests the image server 5 to view medical images, performs various image processing on the medical images received from the image server 5, displays the medical images, analyzes the medical images, emphasizes display of the medical images based on the analysis results, and analyzes the images. Create an interpretation report based on the results.
  • the interpretation WS 3 also supports the creation of interpretation reports, requests registration and viewing of interpretation reports to the interpretation report server 7 , displays interpretation reports received from the interpretation report server 7 , and the like.
  • the interpretation WS3 performs each of the above processes by executing a software program for each process.
  • the interpretation WS 3 includes a medical imaging apparatus 10, which will be described later, and among the above processes, processes other than those performed by the medical imaging apparatus 10 are performed by well-known software programs. omitted.
  • the storage unit 22 is implemented by a HDD (Hard Disk Drive), SSD (Solid State Drive), flash memory, or the like.
  • a medical image program 30 is stored in the storage unit 22 as a storage medium.
  • the CPU 20 reads out the medical image program 30 from the storage unit 22 , expands it in the memory 21 , and executes the expanded medical image program 30 .
  • the acquisition unit 40 acquires a medical image to be diagnosed (hereinafter referred to as a "diagnosis target image") from the image server 5 via the network I/F 25.
  • a medical image to be diagnosed hereinafter referred to as a "diagnosis target image”
  • the image to be diagnosed is a CT image of the liver.
  • the extraction unit 42 inputs the diagnostic target image to the learned model M1.
  • the learned model M1 outputs information specifying a region in which a lesion is present in the input diagnosis target image.
  • the shaded area indicates the lesion.
  • the extraction unit 42 may extract a region including a lesion using a known CAD (Computer-Aided Diagnosis), or may extract a region specified by the user as the region including the lesion.
  • CAD Computer-Aided Diagnosis
  • the analysis unit 44A analyzes each lesion extracted at step S12 as described above, and derives whether the lesion is benign or malignant.
  • step S20A the display control unit 48A performs control to highlight, on the display 23, a lesion with an attribute different from that of the first lesion selected in step S18, among the second lesions, as described above.
  • the lesion display process ends.
  • the medical imaging apparatus 10 includes an acquisition unit 40, an extraction unit 42, an analysis unit 44B, a selection unit 46, a display control unit 48B, and a generation unit 50.
  • the CPU 20 functions as an acquisition unit 40, an extraction unit 42, an analysis unit 44B, a selection unit 46, a display control unit 48B, and a generation unit 50.
  • the generation unit 50 generates a finding sentence summarizing findings of lesions having the same name as the name of the lesion selected by the selection unit 46 .
  • one of the five liver cyst lesions (the lesion indicated by the arrow representing the mouse pointer in the example of FIG. 13) is specified by the user, and the specified lesion name and
  • An example is shown in which a finding statement summarizing the findings of five liver cysts with the same name is generated.
  • the display control unit 48B performs control to display information representing a plurality of lesions extracted by the extraction unit 42 on the display 23, in the same manner as the display control unit 48 according to the first embodiment. In addition, the display control unit 48B performs control to display the observation text generated by the generation unit 50 on the display 23.

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PCT/JP2022/013693 2021-04-07 2022-03-23 医用画像装置、医用画像方法、及び医用画像プログラム Ceased WO2022215530A1 (ja)

Priority Applications (3)

Application Number Priority Date Filing Date Title
EP22784515.3A EP4321100A4 (en) 2021-04-07 2022-03-23 MEDICAL IMAGE DEVICE, MEDICAL IMAGE METHOD, AND MEDICAL IMAGE PROGRAM
JP2023512928A JPWO2022215530A1 (https=) 2021-04-07 2022-03-23
US18/479,817 US20240029252A1 (en) 2021-04-07 2023-10-02 Medical image apparatus, medical image method, and medical image program

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JP2021065375 2021-04-07
JP2021-065375 2021-04-07
JP2021208525 2021-12-22
JP2021-208525 2021-12-22

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WO2024211651A1 (en) * 2023-04-07 2024-10-10 Progenics Pharmaceuticals, Inc. Systems and methods for facilitating lesion inspection and analysis
US12224067B1 (en) 2016-10-27 2025-02-11 Progenics Pharmaceuticals, Inc. Network for medical image analysis, decision support system, and related graphical user interface (GUI) applications
US12243637B2 (en) 2020-07-06 2025-03-04 Exini Diagnostics Ab Systems and methods for artificial intelligence-based image analysis for detection and characterization of lesions
US12243236B1 (en) 2019-01-07 2025-03-04 Exini Diagnostics Ab Systems and methods for platform agnostic whole body image segmentation
US12417533B2 (en) 2019-09-27 2025-09-16 Progenics Pharmaceuticals, Inc. Systems and methods for artificial intelligence-based image analysis for cancer assessment
US12414748B2 (en) 2019-04-24 2025-09-16 Progenics Pharmaceuticals, Inc. Systems and methods for automated and interactive analysis of bone scan images for detection of metastases
US12597127B2 (en) 2021-10-08 2026-04-07 Exini Diagnostics Ab Systems and methods for automated identification and classification of lesions in local lymph and distant metastases
US12602772B2 (en) 2018-01-08 2026-04-14 Progenics Pharmaceuticals, Inc. Systems and methods for rapid neural network-based image segmentation and radiopharmaceutical uptake determination

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Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12224067B1 (en) 2016-10-27 2025-02-11 Progenics Pharmaceuticals, Inc. Network for medical image analysis, decision support system, and related graphical user interface (GUI) applications
US12431246B2 (en) 2016-10-27 2025-09-30 Progenics Pharmaceuticals, Inc. Network for medical image analysis, decision support system, and related graphical user interface (GUI) applications
US12602772B2 (en) 2018-01-08 2026-04-14 Progenics Pharmaceuticals, Inc. Systems and methods for rapid neural network-based image segmentation and radiopharmaceutical uptake determination
US12243236B1 (en) 2019-01-07 2025-03-04 Exini Diagnostics Ab Systems and methods for platform agnostic whole body image segmentation
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US12414748B2 (en) 2019-04-24 2025-09-16 Progenics Pharmaceuticals, Inc. Systems and methods for automated and interactive analysis of bone scan images for detection of metastases
US12417533B2 (en) 2019-09-27 2025-09-16 Progenics Pharmaceuticals, Inc. Systems and methods for artificial intelligence-based image analysis for cancer assessment
US12243637B2 (en) 2020-07-06 2025-03-04 Exini Diagnostics Ab Systems and methods for artificial intelligence-based image analysis for detection and characterization of lesions
US12597127B2 (en) 2021-10-08 2026-04-07 Exini Diagnostics Ab Systems and methods for automated identification and classification of lesions in local lymph and distant metastases
WO2024211651A1 (en) * 2023-04-07 2024-10-10 Progenics Pharmaceuticals, Inc. Systems and methods for facilitating lesion inspection and analysis
US20240354940A1 (en) * 2023-04-07 2024-10-24 Progenics Pharmaceuticals, Inc. Systems and methods for facilitating lesion inspection and analysis

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