Medical Image Analysis Algorithm for Automatic Similar Case Retrieval
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Solution Overview
Problem
Current medical image analysis systems fail to efficiently reference specific areas of interest in pathological-tissue images, leading to increased workload and inefficiency for pathologists during diagnosis.
Innovation Solution
A medical image analysis system that sets sample regions in an image using an algorithm, selects reference images from a database based on these regions, and outputs the selected images to facilitate efficient comparison and diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a pathologist browses pathological-tissue images and refers to relevant information manually, then diagnosis can be performed, but the workload increases and efficiency decreases
Solution Approach 1:
The system pre-processes and stores construction information (cell nucleus images, tissue structure data) alongside pathological-tissue images in a database. When a pathologist views an image, the system automatically retrieves and displays relevant pre-stored information about places of interest, eliminating the need for manual searching through archives or other resources during the diagnosis process
Solution Approach 2:
The system introduces an automated information retrieval intermediary that connects the pathologist's viewing action with relevant diagnostic information. The processing unit acts as a mediator that automatically queries the database for construction information corresponding to the viewed image and presents it to the pathologist, streamlining the information retrieval process
2Loss of information
If the system retrieves similar images from a database, then relevant information can be accessed, but the pathologist cannot always refer to information regarding specific places of interest
Solution Approach 1:
The system segments the pathological-tissue image into multiple regions of interest and extracts construction information from each segment. The processing unit then retrieves and displays relevant information specifically for the viewed place, allowing pathologists to access detailed information about specific areas rather than only general overview information
Solution Approach 2:
The system provides localized information retrieval where the type and detail level of construction information displayed depends on the specific place being viewed. The processing unit adjusts the retrieval parameters based on the viewed image region, ensuring that pathologists receive appropriate level of detail for each specific area of interest
Data Source
AI summary
In parallel with an operation of browsing a pathological-tissue image, retrieval of similar cases from past cases using image information about the pathological-tissue image is automatically performed. An analysis apparatus of the present disclosure includes a first setting unit configured to set sample regions in an analysis target region of an image obtained by imaging of a biologically-originated sample, on the basis of an algorithm; a processing unit configured to select at least one reference image from a plurality of reference images associated with a plurality of cases, on the basis of images of the sample regions; and an output unit configured to output the selected reference image.