Medical Imaging Apparatus Automatic Key Image Selection
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Solution Overview
Problem
Doctors face a significant burden in selecting key images from a large number of medical examination images, as the standard for these images varies by facility and practitioner, making it time-consuming to identify regions of interest for reporting purposes.
Innovation Solution
A medical imaging apparatus equipped with a processor that acquires and compares sample images with examination images to automatically select key images based on category and quality information, displaying the selected images along with non-selected ones for user input and editing, utilizing machine learning and image processing for information extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a doctor manually checks and selects key images from a large number of examination images, then the selection can be done with high accuracy according to medical standards, but it takes a lot of time and creates a heavy burden on the doctor
Solution Approach 1:
The system performs preliminary action by automatically comparing examination images with sample images and extracting key image candidates before the doctor needs to review them. The processor compares image information, determines similarity, and pre-selects key images, so that when the doctor views the results, only the most relevant images are presented, significantly reducing review time while maintaining selection accuracy.
2Loss of time
If the system automatically selects key images using comparison with sample images, then the time for image review is reduced, but the system complexity increases
Solution Approach 1:
The system uses sample images as an intermediary reference standard. Instead of requiring the complex task of manually evaluating all examination images against multiple medical criteria, the system compares examination images against pre-established sample images that represent typical key images. This intermediary approach simplifies the automated selection process while maintaining medical accuracy.
Solution Approach 2:
The system creates a simplified representation of the complex selection criteria by copying the characteristics of sample images into the comparison process. The processor extracts and compares specific image information features from both examination and sample images, creating a manageable copying of the complex medical judgment process that can be automated while maintaining accuracy.
3Ease of operation
If the system displays both selected and non-selected images together, then the user can easily identify and correct selection errors, but the screen complexity and information density increase
Solution Approach 1:
The display interface segments the information by presenting selected key images and non-selected examination images in separate, organized groups. This segmentation allows the user to easily compare and identify selection errors without being overwhelmed by a single mixed list of all images. The processor organizes the displayed information into distinct categories, maintaining ease of operation while managing display complexity.
Data Source
AI summary
At the time of automatic selection of a key image from among a large number of medical examination images, a medical imaging apparatus compares information extracted based on a sample image created in advance with information of an examination image, and performs common category determination and similarity degree determination. As a result of the comparison, the examination image selected to be close to the sample image is set as the key image, and storage processing is performed. The stored key image can be used for medical reports.