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

arXiv: https://arxiv.org/abs/2412.05758 · HTML: https://mlsanity.com/paper/2412.05758/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 44 references that are in the map.
- First posted on arXiv 7 Dec 2024.

## Builds on (most cited first, 3 of 3)

- [A Domain Adaptation Model for Carotid Ultrasound: Image Harmonization, Noise Reduction, and Impact on Cardiovascular Risk Markers](https://mlsanity.com/paper/2407.05163/) (2024)
- [Pushing the Limit of Unsupervised Learning for Ultrasound Image Artifact Removal](https://mlsanity.com/paper/2006.14773/) (2020)
- [Ultrasound Image Enhancement using CycleGAN and Perceptual Loss](https://mlsanity.com/paper/2312.11748/) (2023)

## Abstract (arXiv)

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.