Medical Image Data Association Using Shared Attendant Information
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Solution Overview
Problem
Existing medical image processing systems require manual effort and time for associating multiple examinations, leading to decreased diagnostic efficiency.
Innovation Solution
A medical image processing apparatus and method that automatically associates first and second examination data by using a generating unit to add attendant information to processing result information, linking them through common information for efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual association of multiple examinations is performed, then examination data can be associated, but time consumption and operational effort increase
Solution Approach 1:
The system performs preliminary actions by automatically generating group information and pre-associating examination data using common identifiers (patient ID, study instance UID, series instance UID) before the user needs to reference them. This eliminates the need for manual association at the time of diagnosis, resolving the contradiction between association accuracy and time consumption.
Solution Approach 2:
The system enables self-service by automatically performing the association function using built-in identification fields in the examination data. The apparatus autonomously links multiple examinations through common identifiers without requiring user intervention, thereby maintaining reliability while eliminating time loss.
2Ease of operation
If automatic group information generation is implemented, then operational effort is reduced, but system complexity increases
Solution Approach 1:
The system applies universality by using common identification fields (patient ID, study instance UID, series instance UID) that already exist in standard DICOM examination data structures. By leveraging these universal identifiers across different examinations, the system achieves automatic association without requiring complex proprietary algorithms, thus improving ease of operation while limiting complexity increase.
Solution Approach 2:
The system uses copying by extracting and reusing identification information from existing examination data records. Instead of creating complex new association mechanisms, it copies relevant identifier fields from source examinations and uses them to link related examinations, simplifying the overall system architecture.
Data Source
AI summary
A medical image processing apparatus communicably connected to an imaging apparatus obtains first examination data including image information about a medical image obtained by imaging by the imaging apparatus and first attendant information added to the image information, performs processing of the image information included in the first examination data, and generates second examination data including processing result information obtained by the processing and second attendant information that includes at least part of the first attendant information and is added to the processing result information. The image information and the processing result information are associated by at least part of the first attendant information commonly included in the first attendant information and the second attendant information.