Medical Image Contrast Enhancement via Frequency Decomposition
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Solution Overview
Problem
Medical images, particularly those from full-field digital mammography systems, often suffer from uneven grayscale distribution and noise enhancement, leading to inefficient image processing that can miss edges and distort gray levels, making it difficult for doctors to identify lesions effectively.
Innovation Solution
A method involving image decomposition into low-frequency and high-frequency images, followed by grayscale transformation based on determined parameters to enhance contrast and denoise the image, utilizing techniques like bilateral filtering and wavelet filtering, and reconstructing the transformed images to improve image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional image processing techniques are used to adjust medical images, then some enhancement may be achieved, but image noise is enhanced and edges may be missed
Solution Approach 1:
The patent applies image decomposition to separate the medical image into low-frequency components (containing structural information) and high-frequency components (containing detail and edge information). This segmentation allows different processing strategies to be applied to each component, enabling noise reduction in the low-frequency part while preserving edges in the high-frequency part, thereby resolving the contradiction between noise reduction and edge preservation.
2Reliability
If conventional image processing techniques are used to adjust medical images, then some enhancement may be achieved, but grayscale distribution remains uneven
Solution Approach 1:
The patent implements region-specific grayscale transformation by determining different transformation parameters for different regions of the image based on the low-frequency component. This allows each region to have its grayscale distribution optimized independently, achieving uniform grayscale distribution across the entire image while maintaining the reliability of lesion detection.
3Illumination intensity
If simple image adjustment techniques are used, then processing speed may be maintained, but image contrast enhancement is insufficient
Solution Approach 1:
The patent performs preliminary decomposition of the image into frequency components before contrast enhancement. By pre-processing the image to separate low-frequency and high-frequency components, subsequent contrast enhancement can be applied more efficiently and effectively to the appropriate components, achieving better contrast improvement without sacrificing processing efficiency.
Data Source
AI summary
A system and method for image processing are provided. A pre-processed image may be obtained. The pre-processed image may be decomposed into a low-frequency image and a high-frequency image. At least one grayscale transformation range may be determined based on the low-frequency image. At least one grayscale transformation parameter may be determined based on the at least one grayscale transformation range. The low-frequency image may be transformed based on the at least one grayscale transformation parameter to obtain a transformed low-frequency image. A transformed image may be generated by reconstructing the transformed low-frequency image and the high-frequency image.