Branched Biological Graph Analysis for Real-Time Characteristic Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for analyzing branched biological structures, such as networks of blood vessels, are computationally intensive and often impractical for real-time processing, leading to inaccurate detection of biological characteristics due to the complexity of these structures.
Innovation Solution
An apparatus and method using image processing circuitry to extract graph data from imaging data, representing the structure efficiently, allowing for the detection of biological characteristics with reduced computational resources, enabling real-time analysis and accurate determination of resilience and susceptibility to damage or surgical modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed analysis of the entire complex biological structure is performed, then measurement precision of biological characteristics is improved, but computing resources and processing time increase significantly
Solution Approach 1:
The patent applies segmentation by dividing the complex biological structure into multiple sub-structures or regions of interest. The image processing circuitry processes each segment separately, extracting graph data for each portion independently. This reduces the computational burden on any single processing unit while maintaining overall detection accuracy by aggregating results from multiple segments.
Solution Approach 2:
The patent implements partial action by analyzing only the most relevant or critical portions of the biological structure in detail, while applying simplified analysis to less critical areas. The system identifies key regions that contribute most to biological characteristic detection and focuses computational resources there, achieving acceptable overall accuracy with reduced total computing resources.
2Measurement precision
If detailed analysis of the entire complex biological structure is performed, then measurement precision of biological characteristics is improved, but processing time increases making real-time analysis unfeasible
Solution Approach 1:
By segmenting the biological structure into multiple processable units, the patent enables parallel processing of different regions. The image processing circuitry can simultaneously extract graph data from multiple segments, dramatically reducing total processing time while maintaining comprehensive coverage of the entire structure for accurate biological characteristic detection.
Solution Approach 2:
The patent applies preliminary action by performing preprocessing steps such as image enhancement, noise reduction, and initial feature extraction before the main analysis. Graph data is prepared in advance with pre-computed properties and relationships, so that the subsequent biological characteristic detection can proceed quickly without redundant calculations, enabling real-time or near-real-time analysis.
3Productivity
If only a small portion of the complex structure is analyzed, then processing time and computing resources are reduced, but measurement precision of biological characteristics deteriorates
Solution Approach 1:
The patent implements universality by creating a multi-functional graph data representation that serves multiple purposes. The extracted graph data captures both local structural features and global topological relationships, enabling the same data structure to support both rapid processing and comprehensive analysis. This universal representation allows the system to efficiently query different biological characteristics without reprocessing the raw imaging data.
Solution Approach 2:
The patent introduces graph data as an intermediary between the raw imaging data and the biological characteristic detection. This intermediate representation condenses the complex imaging information into essential structural relationships that can be processed efficiently while retaining sufficient detail for accurate characteristic detection. The graph structure acts as a mediator that bridges the gap between detailed analysis and efficient processing.
Data Source
Figure 1
Figure 2A~2C
Figure 3
AI summary
Examples of the present disclosure relate to an apparatus comprising input circuitry configured to acquire imaging data corresponding to a branched biological structure. The apparatus further comprises image processing circuitry configured to: extract, from the imaging data, a configuration of the branched biological structure; determine graph data indicative of the configuration of the branched biological structure; and detect, based on the graph data, a biological characteristic of the branched biological structure.