Deep model-based optoacoustic image reconstruction (DeepMB)

Christoph Dehner; Vasilis Ntziachristos; Dominik Jüstel; Guillaume Zahnd

doi:10.1117/12.3000893

12 March 2024 Deep model-based optoacoustic image reconstruction (DeepMB)

Christoph Dehner, Vasilis Ntziachristos, Dominik Jüstel, Guillaume Zahnd

Proceedings Volume 12842, Photons Plus Ultrasound: Imaging and Sensing 2024; 128420D (2024) https://doi.org/10.1117/12.3000893
Event: SPIE BiOS, 2024, San Francisco, California, United States

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).

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Christoph Dehner, Vasilis Ntziachristos, Dominik Jüstel, and Guillaume Zahnd "Deep model-based optoacoustic image reconstruction (DeepMB)", Proc. SPIE 12842, Photons Plus Ultrasound: Imaging and Sensing 2024, 128420D (12 March 2024); https://doi.org/10.1117/12.3000893

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