Tumor Classification Visualization Using Multi-Axis Change Mapping
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Solution Overview
Problem
Conventional tumor diagnosis technologies lack comprehensive visualization of tumor risk using multiple indicators and do not provide a user-friendly interface for displaying tumor progression information.
Innovation Solution
A classification assisting device that displays tumor progression information in a coordinate system with multiple axes, using chronological change values of various diagnosis region features, such as size and color, to facilitate easy understanding of tumor risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional tumor diagnosis technologies use a single indicator such as color or size, then the diagnosis process is simple, but the precision of tumor risk identification is insufficient
Solution Approach 1:
The patent transitions from single-indicator diagnosis to multi-dimensional analysis by introducing a scatter diagram with multiple axes. Each axis represents a different feature amount (color, size, shape, texture), enabling comprehensive visualization of tumor characteristics across multiple dimensions simultaneously. This dimensional expansion allows precise tumor risk identification by analyzing the combined information from all features rather than relying on a single indicator.
Solution Approach 2:
The patent segments the tumor diagnosis into separate feature amounts (color, size, shape, texture) and analyzes each independently before integrating them in the scatter diagram. By dividing the complex diagnosis task into manageable segments, the system can process and visualize each feature's chronological change values separately, then combine them to provide comprehensive tumor risk assessment precision.
2Loss of information
If conventional technologies do not comprehensively visualize tumor risk, then the interface remains simple, but the ability to display detailed tumor progression information is insufficient
Solution Approach 1:
The patent uses a scatter diagram that visualizes tumor progression information across multiple dimensions (axes representing different feature amounts). This graphical representation transforms complex multi-dimensional data into an intuitive visual format where doctors can easily perceive tumor risk patterns, chronological changes, and progression trends without overwhelming complexity in the user interface.
Solution Approach 2:
The patent employs color-coded representations in the scatter diagram to indicate different levels of tumor risk or feature characteristics. By using color changes to encode information, the system presents detailed tumor progression data in a visually appealing and easily interpretable manner, enhancing ease of operation while maintaining information completeness.
3Measurement precision
If the system displays detailed multi-indicator tumor information, then the diagnosis precision improves, but the time required for information processing and display increases
Solution Approach 1:
The patent performs preliminary calculations of chronological change values for all feature amounts and prepares the scatter diagram data in advance. By pre-processing the information and organizing it in a structured format, the system reduces real-time processing requirements when displaying tumor progression data, thereby maintaining high diagnosis precision while minimizing time consumption during actual diagnosis operations.
Data Source
AI summary
To display information in a coordinate system having a plurality of axes, based on chronological change values of a plurality of pieces of predetermined diagnosis region information. A classification assisting device includes one or more processors acquiring a chronological change value of each of a plurality of feature amounts relating to a diagnosis region, based on a plurality of diagnosis region images imaged at times different from each other and displaying a scatter diagram in which the chronological change value to be assigned to a first axis and the chronological change value to be assigned to a second axis are selected from the plurality of feature amounts.