Automated Image Registration for 3D Tissue Quantification
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Solution Overview
Problem
Current methods for quantitative analysis of 3-D structural properties of tissues are labor-intensive and inefficient, particularly in inferring 3-D information from 2-D histological sections, due to biased counting methods and time-consuming registration processes in physical disector techniques.
Innovation Solution
A method and system for obtaining and analyzing image pairs from adjacent sections of a specimen, involving image registration, identification of corresponding image fields, and automated counting of objects, which facilitates efficient quantification of 3-D structures by enhancing and detecting stained markers, and providing a tool for image analysis and quantification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical disector techniques are used for quantitative analysis of 3-D structural properties, then measurement precision is improved, but productivity deteriorates due to labor-intensive manual counting and time-consuming registration processes
Solution Approach 1:
The patent replaces manual mechanical counting and registration processes with automated computer-based image analysis systems. The system automatically detects, counts, and registers features across multiple image sections, eliminating labor-intensive manual operations while maintaining quantification accuracy through algorithmic analysis.
Solution Approach 2:
The image analysis system performs self-registration and self-counting operations without human intervention. The automated system independently aligns image sections, identifies features, and generates quantitative results, allowing the analysis process to serve itself rather than requiring continuous human input.
2Measurement precision
If manual registration processes are used to align image sections, then measurement precision is improved through careful alignment, but loss of time increases significantly
Solution Approach 1:
The patent replaces manual alignment operations with automated image registration algorithms that use computer vision techniques to align image sections. The system automatically identifies corresponding features across sections and computes transformation parameters, achieving precise alignment without the time cost of manual adjustment.
Solution Approach 2:
The system performs preliminary automated registration of image sections before quantitative analysis begins. By pre-aligning the images using automated algorithms, the system eliminates the need for time-consuming manual alignment during the analysis phase, saving significant time while maintaining precision.
3Productivity
If automated image analysis is implemented, then productivity is improved through faster processing, but device complexity increases
Solution Approach 1:
The patent implements a multi-functional image analysis system that performs registration, feature detection, counting, and quantification within a single integrated platform. This universal system handles multiple analysis tasks simultaneously, increasing productivity without requiring separate complex devices for each function.
Solution Approach 2:
The system uses digital copies and representations of image data throughout the analysis process, allowing repeated processing and analysis of the same data without physical manipulation. This digital copying approach enables automated re-analysis and verification without increasing physical device complexity.
Data Source
AI summary
Disclosed is a method and a system for obtaining and analyzing image pairs, obtained as sections of specimen. The invention facilitates registration of two corresponding images, one from each section of the specimen. The invention includes performing a registration process of the two images thereby obtaining a mathematical transformation rule and afterwards using said transformation rule for each image field identified in one image allowing that the corresponding image field in the other image may be identified as well. After the corresponding image pairs have been obtained using the method of the present invention, the sections can be assessed, such as by identifying the counting events for at least one type of object on the image fields within at least one corresponding image pair, optionally using automatic means.