Non-linear Color Mapping for Medical Image Contrast
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Solution Overview
Problem
In medical imaging, particularly in neurosurgery, it is challenging for surgeons to differentiate tumors and other objects of interest from surrounding tissue due to poor color differentiation, which can lead to difficulties in making clinical decisions during surgery.
Innovation Solution
A color contrast enhancement system that processes medical images by mapping pixel values in a specified subset of the RGB color space to modified values, using a reference point and a modified color point vector that increases the magnitude of the color point vector, thereby enhancing the perceived contrast of clinically relevant colors in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional image processing is used, then the image processing is simple and fast, but the color contrast between tumors and surrounding tissue remains poor
Solution Approach 1:
The patent applies different color mapping strategies to different regions of the color space. Specifically, it identifies a subset of color values corresponding to tumors and applies a non-linear mapping that enhances contrast only for these relevant colors, while leaving other color regions unchanged. This localized approach improves tumor differentiation without unnecessarily complicating the overall processing.
Solution Approach 2:
The patent transforms color values by changing the parameters of the color space representation. It maps pixel values from the original RGB color space to a modified color space where the contrast between tumor and healthy tissue colors is enhanced. This parameter transformation allows tumors to be differentiated more easily while maintaining the fundamental image structure.
2Loss of information
If non-linear color mapping is applied to enhance contrast, then color differentiation improves, but processing complexity increases
Solution Approach 1:
The patent segments the color space into a subset corresponding to tumor colors and the rest of the color space. By applying the complex non-linear mapping only to the tumor-related color subset rather than the entire color space, it reduces the computational complexity while maintaining the color differentiation capability for clinically relevant colors.
3Reliability
If color values are spread in a specified subset of color space, then tumor visibility improves, but the processing time may increase
Solution Approach 1:
The patent applies the color spreading operation only to a specified subset of the color space that corresponds to tumor colors, rather than processing all color values in the image. This localized processing maintains real-time performance while achieving the desired tumor visibility enhancement.
Data Source
AI summary
An image enhancement system and method for enhancing medical images from a surgical imaging system. Each image pixel has a value in a first three-dimensional color space. A mapping of values in a subset of the first color space is calculated to map each color point in the subset to an enhanced value. The mapping is calculated by selecting a reference point in the subset and, for each color point in the subset, mapping the color point to a modified color value offset from the reference point by the modified color point vector that has the same direction as the color point vector extending from the reference point to the color point, but a greater magnitude. The mapping is applied to the pixel values in the medical image falling in the subset to produce an enhanced image.