Digital Slide Image Deconvolution for Diagnostic Resolution
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Solution Overview
Problem
Digital slide images in pathology are challenging to assess for quality and interpretability due to their large size and variability in staining techniques, leading to difficulties in diagnosis, especially with weak or strong stains, non-standardized characteristics, and poor physical preparation.
Innovation Solution
A system and method that deconvolves digital slide images into separate single-stain images, enhances them through image adjustments and analysis algorithms, and recombines them into improved diagnostic resolution images, facilitating better image quality and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If digital slide images are scanned at diagnostic resolution, then image quality is improved, but file size becomes extremely large making quality assessment difficult
Solution Approach 1:
The patent segments the digital slide image into multiple tiles or regions, allowing selective processing and assessment of individual areas rather than requiring analysis of the entire large-scale image at once. This enables quality assessment of diagnostic-resolution images without requiring simultaneous processing of the complete data set.
2Loss of information
If multiple stains are used on tissue samples, then diagnostic information is improved, but stain variability and non-standardization worsen image quality
Solution Approach 1:
The patent applies parameter changes by adjusting stain intensity, contrast, and color balance through digital image processing. The system normalizes stain parameters across different slides and stains, converting variable stain characteristics into standardized parameter ranges that maintain diagnostic information while achieving consistency.
Solution Approach 2:
The patent replaces physical/chemical stain standardization processes with digital image processing algorithms. Instead of relying on consistent physical staining procedures, the system uses computational methods to normalize and standardize stain appearance digitally, substituting mechanical/chemical precision with algorithmic control.
3Illumination intensity
If strong stains are applied to tissue, then visibility of structures is improved, but heavy coloring reduces image quality
Solution Approach 1:
The patent applies dynamic adjustment of stain intensity through image processing. Rather than using fixed strong or weak stains, the system dynamically optimizes stain visibility parameters based on the specific tissue type, stain characteristics, and diagnostic requirements, allowing adaptability between visibility and quality.
4Stability of the object's composition
If weak stains are applied to tissue, then natural coloring is preserved, but faint coloring reduces diagnostic clarity
Solution Approach 1:
The patent enhances weak stain visibility by adjusting image processing parameters such as contrast enhancement, histogram equalization, and color channel optimization. These parameter changes amplify the diagnostic information in weak stains while preserving their natural characteristics and avoiding artificial appearance.
Data Source
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AI summary
An improved diagnostic resolution of digital slide images is obtained by scanning a first digital slide image at diagnostic resolution that is then deconvolved into separate images with one stain per image. The single stain images are then enhanced with image adjustments and/or processed with image analysis algorithms. The resulting single image data sets from the image analysis algorithms can then be stored. Additionally, the resulting enhanced single images can be recombined into a second digital slide image at diagnostic resolution that is also enhanced.