A new combined prior based reconstruction method for compressed sensing in 3D ultrasound imaging

Muhammad Shahin Uddin; Rafiqul Islam; Murat Tahtali; Andrew J. Lambert; Mark R. Pickering

doi:10.1117/12.2081989

17 March 2015 A new combined prior based reconstruction method for compressed sensing in 3D ultrasound imaging

Muhammad Shahin Uddin, Rafiqul Islam, Murat Tahtali, Andrew J. Lambert, Mark R. Pickering

Proceedings Volume 9419, Medical Imaging 2015: Ultrasonic Imaging and Tomography; 94191B (2015) https://doi.org/10.1117/12.2081989
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Ultrasound (US) imaging is one of the most popular medical imaging modalities, with 3D US imaging gaining popularity recently due to its considerable advantages over 2D US imaging. However, as it is limited by long acquisition times and the huge amount of data processing it requires, methods for reducing these factors have attracted considerable research interest. Compressed sensing (CS) is one of the best candidates for accelerating the acquisition rate and reducing the data processing time without degrading image quality. However, CS is prone to introduce noise-like artefacts due to random under-sampling. To address this issue, we propose a combined prior-based reconstruction method for 3D US imaging. A Laplacian mixture model (LMM) constraint in the wavelet domain is combined with a total variation (TV) constraint to create a new regularization regularization prior. An experimental evaluation conducted to validate our method using synthetic 3D US images shows that it performs better than other approaches in terms of both qualitative and quantitative measures.

Citation Download Citation

Muhammad Shahin Uddin, Rafiqul Islam, Murat Tahtali, Andrew J. Lambert, and Mark R. Pickering "A new combined prior based reconstruction method for compressed sensing in 3D ultrasound imaging", Proc. SPIE 9419, Medical Imaging 2015: Ultrasonic Imaging and Tomography, 94191B (17 March 2015); https://doi.org/10.1117/12.2081989

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