SSI-Net: A hybrid physics-constrained deep learning framework for quantitative ultrasound speed-of-sound reconstruction
By embedding an exact wave solver into a trainable architecture, SSI‑Net combines the representational capacity of deep learning with strict physical consistency. It provides a robust, efficient, and clinically translatable solution for quantitative SoS imaging, offering a promising tool for tissue characterization in diagnostic ultrasound.
Authors
- Yangjie Sheng
- Zhangshuo Gao
- Qian Jiang
- Zheng Sun
Institutions
- North China Electric Power University (CN)
Publication Details
- Journal
- Physics in Medicine and Biology
- Published
- 2026-03-17
- DOI
- https://doi.org/10.1088/1361-6560/ae5374
- Primary Topic
- Ultrasound Imaging and Elastography
- Type
- article
- Field-Weighted Citation Impact
- 0.00