Graph-Based Microscopic Image Analysis for Cancer Diagnosis
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Solution Overview
Problem
Current cancer diagnosis and prognosis methods relying on visual examination of stained slides are time-consuming and inconsistent, and there is a need for efficient and reliable extraction of parameters from microscopic images for accurate analysis.
Innovation Solution
A system that processes microscopic image data by determining vertices representing entities of interest, generating graphs based on these vertices, and identifying vertex sets to classify and rate tissue portions, allowing for the generation of graphical representations such as heat maps for improved analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual examination of stained slides is used for cancer diagnosis, then pathologists can assess tissue morphology, but the process is time-consuming and results are inconsistent
Solution Approach 1:
The patent replaces the mechanical visual examination process with an automated image processing system. The system uses computational algorithms to analyze microscopic images, extract features, and generate diagnoses, thereby eliminating the time-consuming and inconsistent manual assessment while maintaining diagnostic accuracy through standardized automated evaluation.
Solution Approach 2:
The patent creates digital copies of microscopic slides and analyzes these copies using image processing algorithms. By working with digital representations rather than physical slides, the system enables rapid, consistent, and reproducible analysis without the time constraints of manual examination, achieving both speed and reliability improvements.
2Productivity
If automated image processing is applied to extract structures from images, then analysis speed increases, but reliable parameter extraction remains challenging
Solution Approach 1:
The patent segments the image processing task into multiple stages: image acquisition, feature extraction, graph construction, and parameter calculation. By dividing the complex analysis into manageable segments, the system achieves both high processing speed through automated algorithms and precise parameter extraction through specialized computational methods that analyze spatial relationships and density distributions.
Solution Approach 2:
The patent transforms 2D microscopic images into 3D spatial graphs by adding depth information through vertex sets and spatial coordinate analysis. This dimensional transformation enables the system to capture complex spatial relationships and density distributions, improving parameter extraction accuracy while maintaining high processing speed through efficient computational algorithms.
Data Source
AI summary
Disclosed is a system for analysis of microscopic image data acquired from biological cells. The system includes a data processing system which is configured to read the image data and determine a plurality of vertices, wherein each of the vertices represents a location of an entity of interest within a region of interest of the image data. The data processing system generates a plurality of graphs, wherein for each of the graphs, the generation of the respective graph includes generating a plurality of edges, wherein each of the edges has two of the plurality of vertices associated therewith. For each of the graphs one or more vertex sets are identified, each of which consisting of one or more of the plurality of vertices. The data processing system further determines, for each of the graphs, a number of the identified vertex sets.