Co-registered Tissue Image Alignment via Tile Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The computational intensity of co-registering high-resolution digital images of tissue slices stained with different biomarkers makes precise alignment impractical, leading to imprecise co-registration when using low-resolution structures for segmentation.
Innovation Solution
A system that co-registers and displays digital images by generating low-resolution images from high-resolution ones, defining shapes within these images, determining corresponding regions, and interpolating co-registration parameters to align higher resolution images in a common coordinate system, allowing precise alignment without segmenting entire high-resolution images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If segmentation is performed on low-resolution superimages to find structures for co-registration, then computational feasibility is achieved, but co-registration precision deteriorates
Solution Approach 1:
The patent divides the high-resolution image into multiple overlapping tiles or blocks. Each tile is processed independently to identify local structures and features, which are then integrated to achieve precise co-registration across the entire high-resolution image without requiring full-image segmentation
Solution Approach 2:
The patent applies different processing strategies to different regions of the image. High-resolution local structures are preserved and used for precise feature matching in critical areas, while lower-resolution overview provides computational efficiency for global alignment, creating a multi-scale approach that optimizes both precision and feasibility
2Measurement precision
If segmentation is performed on entire high-resolution images to find corresponding structures, then co-registration precision is improved, but computational intensity becomes infeasible
Solution Approach 1:
The patent segments the high-resolution image into manageable tiles that can be processed independently and in parallel. This reduces the computational burden of segmenting and comparing entire high-resolution images while maintaining the ability to identify corresponding structures through tile-level feature matching and integration
Solution Approach 2:
The patent processes only selected regions or tiles of the high-resolution image rather than the entire image. By focusing computational resources on key regions containing diagnostic structures and using lower-resolution processing for less critical areas, the system achieves sufficient co-registration precision with reduced computational intensity
3Measurement precision
If multiple high-resolution digital images are co-registered and displayed simultaneously, then diagnostic accuracy is improved, but system complexity increases
Solution Approach 1:
The patent implements a unified co-registration and display system that can handle multiple high-resolution images with different stains and resolutions. The system uses universal feature extraction and matching algorithms that work across different image types, and provides multiple display modes (side-by-side, overlay, etc.) within a single interface, reducing the need for separate specialized tools
Data Source
AI summary
A method for co-registering images of tissue slices stained with different biomarkers displays a first digital image of a first tissue slice on a graphical user interface such that an area of the first image is enclosed by a frame. Then a portion of a second image of a second tissue slice is displayed such that the area of the first image enclosed by the frame is co-registered with the displayed portion of the second image. The displayed portion of the second image has the shape of the frame. The tissue slices are both z slices of a tissue sample taken at corresponding positions in the x and y dimensions. The displayed portion of the second image is shifted in the x and y dimensions to coincide with the area of the first image that is enclosed by the frame as the user shifts the first image under the frame.