Biological Tissue Image Reconstruction via Spectral Classification
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Solution Overview
Problem
Current pathological diagnosis methods, such as immunostaining, face challenges with reproducibility and the inability to visualize multiple constituent substances at a cellular level, limiting their effectiveness in accurately identifying cancerous tissues.
Innovation Solution
A method and apparatus that apply a classification algorithm to measured spectrum data from biological tissues, utilizing spatial distribution information and peak component intensity to reconstruct high-resolution biological tissue images, integrating both spectrum and morphological information for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If immunostaining method is used to visualize constituent substances, then specific antigen proteins can be detected, but reproducibility is poor due to antibody instability and difficult control of antigen-antibody reaction efficiency
Solution Approach 1:
The patent replaces the biochemical immunostaining mechanism with a physical measurement mechanism (Raman spectroscopy or SIMS) that measures spectral characteristics of constituent substances directly, eliminating the need for antibodies and their associated reproducibility issues while maintaining detection capability
Solution Approach 2:
The patent changes the measurement parameter from antibody binding intensity to spectral characteristics (Raman shifts or mass spectra), which are intrinsic properties of the substances themselves and do not depend on unstable biological reagents, thereby improving reproducibility
2Adaptability or versatility
If immunostaining method is used for detecting multiple constituent substances, then visualization capability is limited, but the need for detecting several tens or more kinds of substances cannot be met
Solution Approach 1:
The patent employs a universal measurement platform (Raman spectroscopy or SIMS) that can detect multiple constituent substances simultaneously through their unique spectral or mass spectral fingerprints, eliminating the need for multiple separate immunostaining procedures and enabling comprehensive analysis of dozens of substances in a single measurement
Solution Approach 2:
The patent adds a spectral dimension to the measurement, transforming the problem from detecting multiple substances through multiple separate procedures to detecting them simultaneously through their distinctive spectral signatures, thereby increasing versatility without proportionally increasing complexity
3Area of stationary object
If tissue-level observation is performed, then overall tissue structure can be visualized, but cellular-level expression distribution of constituent substances cannot be observed
Solution Approach 1:
The patent segments the tissue into individual cellular or subcellular regions and measures spectral characteristics at each segmented location, enabling both comprehensive tissue-level coverage and precise cellular-level resolution by processing measurements from multiple discrete points across the tissue sample
Data Source
AI summary
Provided are a method of reconstructing a biological tissue image, and a method and apparatus for acquiring a biological tissue image, which allow a biological tissue to be identified with higher accuracy than ever before. The reconstruction of the biological tissue image is performed by measuring spectra having a two-dimensional distribution correlated with a biological tissue section, and acquiring a biological tissue image from the two-dimensional measured spectra through utilization of the measured spectra and an classifier.