Basis Conversion for Medical Image Reconstruction
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Solution Overview
Problem
Existing technologies face challenges in efficiently processing and reconstructing medical images, particularly in handling time-series MRI data and extracting correlations among them.
Innovation Solution
An information processing apparatus that performs basis conversion on signal data to calculate multiple bases, selects specific bases with lower contribution rates, and executes data processing using these null bases to achieve null-space-constraint reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional basis conversion is used to process time-series MRI data, then computational complexity increases, but image reconstruction quality deteriorates due to noise and loss of high-correlation information
Solution Approach 1:
The patent segments the basis set into two distinct groups: principle bases (high contribution rate) and null bases (low contribution rate). This segmentation allows selective processing where null bases are used for noise reduction while principle bases preserve high-correlation information, thereby improving image reconstruction quality without requiring complex full-basis processing
Solution Approach 2:
The patent extracts and isolates the null bases from the complete basis set, separating them from principle bases. By taking out only the necessary null bases for noise reduction while excluding principle bases that contain high-correlation information, the method reduces computational complexity while maintaining reconstruction quality
2Reliability
If all bases are used in data processing, then more information is captured, but noise is also amplified and computational load increases
Solution Approach 1:
The patent applies different quality treatments to different parts of the basis set. Null bases are selectively used for noise reduction in specific frequency domains, while principle bases are preserved for maintaining high-correlation information. This local quality approach ensures reliable information preservation without uniformly processing all bases, thereby reducing computational load
3Object-affected harmful factors
If conventional reconstruction methods are used, then computational simplicity is maintained, but noise reduction capability is insufficient
Solution Approach 1:
The patent converts the typically discarded null bases, which contain noise, into a beneficial tool for noise reduction. By selectively applying null bases in the reconstruction process rather than discarding them, the method transforms what was previously harmful (noise-containing bases) into a useful component for eliminating noise from the final image, achieving superior noise reduction without excessive processing complexity
Data Source
AI summary
According to one embodiment, an information processing apparatus includes processing circuitry. The processing circuitry calculates a plurality of bases by performing a basis conversion on signal data. The processing circuitry selects one or more specific bases with contribution rates lower than a reference from among the bases. The processing circuitry executes data processing utilizing the specific bases.