Stain-Based Color Transform Compression for Digital Pathology Slides
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Solution Overview
Problem
Digital pathology slide images with significant visual content are difficult to compress while maintaining high visual quality, due to their large size and complex color properties, which hinders efficient storage and streaming.
Innovation Solution
Pre-computation of optimized color transforms using training images for specific staining methods, followed by mapping and compressing input images using these transforms, employing techniques like PCA to improve rate-distortion performance and enable efficient image streaming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lossy compression techniques are used to compress digital pathology slide images, then storage efficiency and streaming capability are improved, but visual quality deteriorates
Solution Approach 1:
The patent applies parameter changes by transforming the color space of pathology images from standard RGB to optimized color transforms (such as YCbCr, LAB, or custom transforms) that better represent the visual characteristics of stained tissue. This parameter transformation allows compression algorithms to achieve better rate-distortion performance by exploiting the specific color distribution and redundancy patterns in stained pathology images, thereby maintaining visual quality while improving compression efficiency
Solution Approach 2:
The patent implements preliminary action by pre-computing and storing optimized color transform matrices that are specific to different staining methods (such as H&E, PAS, or immunohistochemistry stains). These pre-computed transforms are applied to incoming images before compression, allowing the system to quickly adapt to different stain types without performing complex computations in real-time, thus maintaining both speed and quality
2Measurement precision
If high resolution scanning is used to digitize tissue samples, then diagnostic information is improved, but image size increases
Solution Approach 1:
The patent applies segmentation by dividing the large high-resolution pathology slide image into smaller manageable units or tiles that can be processed and compressed independently. This segmentation allows the system to maintain the diagnostic information contained in the high-resolution image while reducing the overall data volume through selective compression of different regions based on their visual complexity and diagnostic importance
Solution Approach 2:
The patent uses parameter changes by applying color space transformations and adaptive quantization to reduce the bit-depth and color precision of image regions that do not contain critical diagnostic information. This selective parameter adjustment maintains the necessary diagnostic detail in key areas while reducing the overall image size through aggressive compression in less critical regions
Data Source
AI summary
A novel and useful method and system of optimized image compression of digital pathology slide images. The optimized image compression mechanism exploits the special color properties of the stained tissue represented by the digital pathology slides and provides an image compression algorithm having improved rate-distortion performance. Optimized color transforms are pre-computed using training sets of pathology slide image scan data for each stain type. The optimized color transforms are used to compress input slide image scans resulting in more efficient image streaming enabling users to review extremely large digital slide scans from any connected location, such as in a hospital, satellite center, home or on a mobile telephone.