A Detail-Preserving Ultrasound Speckle Reduction Method Based on Complementary Information

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Image Processing

Background:

• Speckle noise is an inherent artifact in ultrasound (US) imaging, degrading image quality and hindering subsequent analysis.
• Existing speckle reduction techniques often fail to preserve fine image details, creating a trade-off between noise suppression and structural fidelity.

Purpose of the Study:

• To develop an advanced speckle reduction method for ultrasound images that effectively denoises while preserving crucial image details.
• To introduce a novel regularization technique that leverages complementary information for improved image reconstruction.

Main Methods:

• A new method, Sparsity and Second-order Hessian (SASH) regularization, is proposed.
• SASH incorporates spatial continuity as a structural prior, using second-order Hessian derivatives to enforce smoothness and directional consistency.
• The method enhances high-frequency information by extending the concept of sparsity to better preserve image details.

Main Results:

• The SASH method demonstrates a superior balance between noise reduction and detail retention compared to existing approaches.
• Leverages synergistic effects of sparsity and structural priors for effective speckle removal.

Conclusions:

• SASH significantly improves denoising and edge preservation in ultrasound images.
• This method provides a foundation for advanced post-processing techniques like image segmentation and feature extraction.