Emulating Clinical Quality Muscle B-mode Ultrasound Images from Plane Wave Images Using a Two-Stage Machine Learning Model

Reed Chen; Courtney Trutna Paley; Wren Wightman; Lisa Hobson-Webb; Yohei Harada; Felix Jin; Ouwen Huang; Mark Palmeri; Kathryn Nightingale

arXiv · 2412.05758

Emulating Clinical Quality Muscle B-mode Ultrasound Images from Plane Wave Images Using a Two-Stage Machine Learning Model

Reed Chen·Courtney Trutna Paley·Wren Wightman·Lisa Hobson-Webb·Yohei Harada·Felix Jin·Ouwen Huang·Mark Palmeri·Kathryn Nightingale

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Abstract

Research ultrasound scanners such as the Verasonics Vantage often lack the advanced image processing algorithms used by clinical systems. Image quality is even lower in plane wave imaging - often used for shear wave elasticity imaging (SWEI) - which sacrifices spatial resolution for temporal resolution. As a result, delay-and-summed images acquired from SWEI have limited interpretability. In this project, a two-stage machine learning model was trained to enhance single plane wave images of muscle acquired with a Verasonics Vantage system. The first stage of the model consists of a U-Net trained to emulate plane wave compounding, histogram matching, and unsharp masking using paired images. The second stage consists of a CycleGAN trained to emulate clinical muscle B-modes using unpaired images. This two-stage model was implemented on the Verasonics Vantage research ultrasound scanner, and its ability to provide high-speed image formation at a frame rate of 28.5 +/- 0.6 FPS from a single plane wave transmit was demonstrated. A reader study with two physicians demonstrated that these processed images had significantly greater structural fidelity and less speckle than the original plane wave images.

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Reed Chen, Courtney Trutna Paley, Wren Wightman, Lisa Hobson-Webb, Yohei Harada, Felix Jin, Ouwen Huang, Mark Palmeri, Kathryn Nightingale. 2024-12-07. Emulating Clinical Quality Muscle B-mode Ultrasound Images from Plane Wave Images Using a Two-Stage Machine Learning Model. https://arxiv.org/abs/2412.05758

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