Microscopy Image Normalization for Structure Recognition Accuracy
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Solution Overview
Problem
Current image processing algorithms for microscopy images face challenges in accuracy due to variations in structure appearance caused by imaging parameters and type-specific properties, leading to incorrect segmentation and recognition of structures.
Innovation Solution
A method that adjusts image properties such as size, contrast, orientation, and brightness to normalize the appearance of structures in microscopy images, allowing for improved processing by aligning them with reference values used in training data, thereby enhancing the accuracy of image processing algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing algorithms are applied directly to microscopy images with varying structure appearances, then processing speed is maintained, but accuracy and reliability of structure recognition deteriorate
Solution Approach 1:
The patent applies preliminary normalization actions to microscopy images before they are processed by image processing algorithms. By pre-adjusting image properties such as brightness, contrast, size, and orientation to match reference values from training data, the system prepares the images in advance to ensure consistent structure appearance. This preliminary action improves recognition accuracy without adding complexity during the actual processing phase.
2Reliability
If multiple image properties are adjusted for each structure type, then consistency with training data improves, but processing time increases
Solution Approach 1:
The patent systematically changes multiple image parameters (brightness, contrast, size, orientation) to normalize structure appearances across different microscopy images. By adjusting these parameters to match reference values established during training data creation, the system ensures that structures appear consistently regardless of variations in imaging conditions. This comprehensive parameter adjustment approach maintains high processing reliability while managing processing time through automated normalization procedures.
Data Source
AI summary
Various examples relate to techniques for the image processing of microscopy images which image a plurality of types of a structure. The plurality of types have different appearances.