Towards in-vivo ultrasound-histology: Plane-waves and generative adversarial networks for pixel-wise speed of sound reconstruction
Pavlov I, Prado E, Navab N, Zahnd G (2019)
Publication Type: Conference contribution
Publication year: 2019
Journal
Publisher: IEEE Computer Society
Book Volume: 2019-October
Pages Range: 1913-1916
Conference Proceedings Title: IEEE International Ultrasonics Symposium, IUS
Event location: Glasgow, GBR
ISBN: 9781728145969
DOI: 10.1109/ULTSYM.2019.8925722
Abstract
Ultrasound imaging is a well-established modality, widely used for in vivo real time examination. Nevertheless, the ability of conventional ultrasound techniques is limited by the fact that different biological tissues are sometimes represented with the same image brightness, thus hindering visual - as well as automatic - identification. Especially valuable for tissue differentiation is the pressure wave velocity, which can be measured with ultrasound. Deep-learning-based methods carry a possibility to overcome such limitations and enable robust signal-based tissue identification. Such methods have been successfully applied to tackle various challenges of medical imaging research. The aim of the present work is to propose a Generative Adversarial Network (GAN) pipeline towards pixel-wise speed of sound (SoS) reconstruction from plane-wave ultrasound raw channel signals corresponding to three firing angles. The network is trained on a novel synthetic dataset focusing on complex geometry, generated with K-Wave. Results demonstrate a promising performance, with average (± STD) absolute SoS reconstruction errors of 38 ±54 m/s in real time at 114 fps. The proposed approach paves the way towards GAN-based ultrasound histology.
Involved external institutions
Germany (DE)How to cite
APA:
Pavlov, I., Prado, E., Navab, N., & Zahnd, G. (2019). Towards in-vivo ultrasound-histology: Plane-waves and generative adversarial networks for pixel-wise speed of sound reconstruction. In IEEE International Ultrasonics Symposium, IUS (pp. 1913-1916). Glasgow, GBR: IEEE Computer Society.
MLA:
Pavlov, Ivan, et al. "Towards in-vivo ultrasound-histology: Plane-waves and generative adversarial networks for pixel-wise speed of sound reconstruction." Proceedings of the 2019 IEEE International Ultrasonics Symposium, IUS 2019, Glasgow, GBR IEEE Computer Society, 2019. 1913-1916.
BibTeX: Download