Medical Image Frequency Analysis for Target Tissue Isolation
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Solution Overview
Problem
Conventional medical image analysis techniques face accuracy issues when non-target tissues are included in the region of interest (ROI), leading to deteriorated determination accuracy for target tissues like liver tissue.
Innovation Solution
A medical information processing apparatus that applies frequency conversion to medical images, determines similarity of spectral values in the frequency space with characteristic data, and designates target areas based on this similarity, effectively isolating features of the target tissue by extracting spectral values from designated areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency conversion is applied to medical images to extract spectral values, then target tissue features can be extracted even when non-target tissues are present, but the complexity of the processing apparatus increases
Solution Approach 1:
The patent divides the frequency space into multiple regions and selectively extracts spectral values only from regions corresponding to target tissues. This segmentation approach allows the system to process only relevant frequency components, maintaining high determination accuracy while reducing unnecessary computational complexity from processing entire frequency spectra.
Solution Approach 2:
The patent applies different processing strategies to different regions of the frequency space. By identifying and focusing computational resources on local regions that contain target tissue information, the system achieves high measurement precision without uniformly processing all frequency components, thus avoiding excessive complexity.
2Loss of information
If the entire frequency space is processed to extract all spectral values, then complete tissue information is obtained, but processing time and computational load increase
Solution Approach 1:
The patent extracts only the necessary spectral values from specific regions of the frequency space that correspond to target tissues, rather than processing the entire frequency spectrum. This selective extraction maintains completeness of relevant tissue information while significantly reducing processing time and computational load by excluding irrelevant frequency components.
Solution Approach 2:
The patent applies partial action by processing only the portion of the frequency space that contains useful diagnostic information. Instead of exhaustively analyzing all frequency components, the system focuses on partial regions that are sufficient for accurate tissue characterization, thereby reducing processing time while maintaining information completeness.
Data Source
AI summary
A medical information processing apparatus according to an embodiment includes a storage and processing circuitry. The storage is configured to store therein, for each point of a frequency space represented by a plurality of pieces of first frequency component data acquired by applying frequency conversion to data inside regions of interest set to medical images, characteristic data representing a tendency of spectral values that appear at the point. The processing circuitry is configured to acquire second frequency component data by applying frequency conversion to a medical image to be processed, to determine similarity of a spectral value at each point of a frequency space represented by the second frequency component data, with the characteristic data, and to designate a target area in the frequency space represented by the second frequency component data based on the result of the determination.