@inproceedings{93a9b54a5d3b4e8b887351eeba113b9e,
title = "Deep model-based optoacoustic image reconstruction (DeepMB)",
abstract = "Multispectral optoacoustic tomography requires real-time image feedback during clinical use. Herein, we present DeepMB, a deep learning framework to express the model-based reconstruction operator with a deep neural network and reconstruct high-quality optoacoustic images from arbitrary experimental input data at speeds that enable live imaging (31ms per image).",
keywords = "Inverse problems, Model-based reconstruction, Multispectral Optoacoustic Tomography (MSOT), Real-time imaging, Synthesized training data",
author = "Christoph Dehner and Vasilis Ntziachristos and Dominik J{\"u}stel and Guillaume Zahnd",
note = "Publisher Copyright: {\textcopyright} 2024 SPIE.; Photons Plus Ultrasound: Imaging and Sensing 2024 ; Conference date: 28-01-2024 Through 31-01-2024",
year = "2024",
doi = "10.1117/12.3000893",
language = "English",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Oraevsky, {Alexander A.} and Wang, {Lihong V.}",
booktitle = "Photons Plus Ultrasound",
}