Medical Image Tissue Quantification for Consistent Organ Evaluation
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Solution Overview
Problem
Existing medical image evaluation methods for organs, particularly in time-sensitive situations like organ transplantation, suffer from inaccuracies due to subjective interpretation and variability among evaluators, necessitating improved accuracy and efficiency.
Innovation Solution
A method involving extracting target partial images from medical images, identifying and categorizing target tissues based on visual conditions, and calculating feature quantities to provide objective numerical information, using machine learning and image analysis algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual evaluation of medical images is performed by human evaluators, then flexibility and adaptability are maintained, but evaluation accuracy fluctuates due to subjectivity and skill differences
Solution Approach 1:
The patent replaces the manual mechanical evaluation process with an automated image processing system that uses algorithms to extract features and calculate quantitative metrics from medical images, eliminating human subjectivity and skill variability while maintaining measurement precision and evaluation consistency
Solution Approach 2:
The system enables self-service evaluation by automatically processing medical images through feature extraction and quantitative calculation without requiring human evaluators, allowing the system to serve itself in producing consistent and accurate evaluation results
2Measurement precision
If comprehensive analysis of entire medical images is performed, then evaluation accuracy is improved, but processing time increases
Solution Approach 1:
The patent segments the medical image into multiple regions of interest and focuses analysis on specific areas containing target tissues, allowing comprehensive evaluation of critical features while reducing overall processing time by avoiding unnecessary analysis of entire image areas
Solution Approach 2:
The system extracts and isolates specific features and regions of interest from the complete medical image, concentrating computational resources on analyzing only the relevant portions that contribute to evaluation accuracy, thereby reducing processing time while maintaining precision
Data Source
AI summary
The present disclosure relates to a method for processing a medical image performed by a processor. The method comprises: obtaining a medical image showing an organ; extracting, from the medical image, at least one target partial image containing an area occupied by the organ with a ratio equal to or greater than a predetermined ratio with respect to a total area of the at least one target partial image; identifying, in the at least one target partial image, at least one target tissue having a region satisfying a predetermined visual condition; calculating a feature quantity of the at least one target tissue; and outputting a processing result including the at least one target partial image and the feature quantity of the at least one target tissue.