Medical Image Noise Reduction via Wavelet Decomposition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current x-ray diagnostic devices face challenges in reducing noise in 2D and 3D medical images, leading to poor signal-to-noise ratios and reduced image quality, which can complicate diagnoses and require increased radiation doses to improve image clarity, violating regulatory limits.
Innovation Solution
A method involving one-off calibration of signal-dependent noise, separation of signal and noise components using non-linear wavelet decomposition, and adaptive processing to reconstruct noise-reduced images, applicable to both 2D and 3D data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the radiation dose is increased to improve the signal-to-noise ratio and image quality, then the image quality improves, but the radiation exposure to patients and medical personnel increases beyond regulatory limits
Solution Approach 1:
The patent extracts and removes the noise component from the x-ray image signal through wavelet decomposition and thresholding techniques. By separating the signal into different frequency bands and selectively eliminating noise components, the method improves image quality without requiring increased radiation exposure.
Solution Approach 2:
The patent applies noise filtering and wavelet decomposition procedures during the image reconstruction phase before final image display. This preliminary processing removes noise artifacts before they degrade diagnostic quality, allowing optimal image quality at lower radiation doses.
2Measurement precision
If conventional smoothing filters are applied to reduce noise in 3D reconstruction, then some noise reduction is achieved, but meaningful noise reduction is not guaranteed and image detail may be lost
Solution Approach 1:
The patent segments the image signal into multiple frequency bands using wavelet decomposition. Different processing strategies can be applied to different frequency components, allowing noise reduction in high-frequency bands while preserving important diagnostic details in low-frequency bands.
Solution Approach 2:
The patent applies adaptive thresholding and noise filtering that varies locally across the image based on regional noise characteristics and signal importance. This allows aggressive noise reduction in homogeneous regions while preserving edges and fine structures in diagnostically critical areas.
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
This approach effectively reduces noise in medical images, enhancing image quality, allowing for better diagnosis and reduced radiation exposure for both patients and medical professionals while maintaining image clarity.
Implementation Method 1
an x-ray emitter 3... The x-ray source 3 emits a ray bundle 10 emanating from the ray focus of its radiographic source
Implementation Method 2
the separation of the image components to be undertaken by a filter with non-linear wavelet decomposition
Data Source
AI summary
The invention relates to a method for presentation of medical images by a reproduction facility of a diagnostic device with suppression of the noise with the following steps: one-off calibration of the signal-dependent noise; separation of the signal and noise components in the image; adaptation of the two components according to set parameters; and composition of the signals.