Spectral Pseudo-Color Imaging for Tumor Boundary Detection
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Solution Overview
Problem
Existing methods for determining tumor tissue boundaries in pathological specimens, such as visual observation by pathologists or X-ray imaging, struggle with accuracy, especially for inconspicuous lesions, and are limited by the high cost and accessibility of X-ray devices.
Innovation Solution
An image processing method that analyzes samples based on spectral characteristics at different wavelengths, involving image capture within a preset optical waveband, pseudo-color image generation, and region division to accurately determine tumor tissue regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual observation by pathologists is used to determine tumor tissue boundaries, then the method is simple and accessible, but the accuracy is low especially for inconspicuous lesions
Solution Approach 1:
The patent applies pseudo-color processing to convert grayscale images into color-enhanced images that highlight different tissue types. This color transformation makes inconspicuous lesions more visible and distinguishable, directly addressing the accuracy problem while maintaining the simplicity of the imaging device
Solution Approach 2:
The patent introduces an image processing system as an intermediary between the simple imaging device and the pathologist's analysis. This intermediary enhances the image quality and provides automated region division, bridging the gap between simple accessibility and high accuracy requirements
2Measurement precision
If X-ray imaging is used to determine tumor tissue boundaries, then the accuracy is improved, but the device cost is high and accessibility is limited
Solution Approach 1:
The patent replaces expensive X-ray devices with a cheaper optical imaging system. By using standard cameras or endoscopes combined with image processing algorithms, the system achieves comparable or superior accuracy at a fraction of the cost, making the technology widely accessible
Solution Approach 2:
The patent substitutes the mechanical X-ray imaging system with an optical imaging system. By replacing the complex X-ray hardware with simpler optical components and using computational methods for image enhancement, the system maintains high accuracy while dramatically reducing device complexity and cost
3Adaptability or versatility
If conventional imaging methods are used, then the device is simple and accessible, but the ability to recognize inconspicuous lesions is poor
Solution Approach 1:
The patent segments the tissue regions by automatically dividing the image into different areas based on spectral characteristics. This segmentation creates distinct visual regions for different tissue types, making even subtle or inconspicuous lesions clearly distinguishable from surrounding tissues
Solution Approach 2:
The patent changes the spectral parameters of the image by processing at multiple wavelengths and applying pseudo-color transformations. This parameter transformation enhances the contrast between different tissue types, improving the visibility of inconspicuous lesions while maintaining device simplicity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves the accuracy of pathological sampling by enabling precise identification of tumor tissue boundaries, reducing reliance on costly X-ray devices, and enhancing the efficiency of medical diagnostics.
Implementation Method 1
analyze a sample according to spectral characteristics of a first sample at different wavelengths
Data Source
AI summary
An image processing method and apparatus are provided. The method includes: acquiring a sample image, the sample image comprising an image obtained by image-capturing a sample within a preset optical waveband; processing a first image corresponding to at least one preset wavelength within the preset optical waveband in the sample image, to obtain a pseudo-color image; performing region division on the sample image according to a difference in sample element types in the sample image to obtain a region division result, the sample element types comprising a recognition element type; and determining an image region comprising the recognition element type from the sample image based on the pseudo-color image and the region division result.