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Ultrasound Image Despeckling Using Stochastic Distance-Based BM3D.

Cid A N Santos, Diego L N Martins, Nelson D A Mascarenhas

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|March 24, 2017

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This study introduces novel stochastic distances for ultrasound image despeckling. These new methods improve the Block-Matching Collaborative Filtering (BM3D) algorithm for clearer medical images.

Area of Science:

Medical Imaging
Signal Processing
Statistical Modeling

Background:

Ultrasound imaging is crucial in medical diagnostics, but speckle noise degrades image interpretability.
Patch-based methods like Block-Matching Collaborative Filtering (BM3D) are advanced techniques for ultrasound despeckling.
Existing methods often rely on Euclidean distance for patch comparison, which may not be optimal for all noise types.

Purpose of the Study:

To develop and evaluate new stochastic distance measures for the Fisher-Tippett distribution.
To integrate these novel distances into a modified BM3D algorithm for enhanced ultrasound image despeckling.
To improve the filtering of noise in log-compressed ultrasound images.

Main Methods:

Derivation of new stochastic distances for the Fisher-Tippett distribution using established statistical divergences.

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Implementation of a modified Block-Matching Collaborative Filtering (BM3D) algorithm incorporating the novel patch distance measures.

Application and evaluation of the algorithm on simulated, synthetic, and real ultrasound images.

Main Results:

The proposed stochastic distances effectively serve as patch distance measures within the modified BM3D framework.
The developed algorithm demonstrates superior performance in filtering speckle noise compared to existing state-of-the-art methods.
Significant improvements in the interpretability of processed ultrasound images were observed across various datasets.

Conclusions:

The novel stochastic distances derived from statistical divergences offer a powerful alternative to Euclidean distance for ultrasound despeckling.
The modified BM3D algorithm incorporating these distances achieves state-of-the-art results in reducing speckle noise.
This approach holds significant potential for improving the quality and diagnostic value of ultrasound medical imaging.