Improving quality of less-view breast photoacoustic tomography reconstruction using deep learning neural networks

Bruno De Santi; Fazael Ayatollahi; Felix Lucka; Navchetan Awasthi; Ben Cox; Srirang Manohar

doi:10.1117/12.2650604

27 March 2023 Improving quality of less-view breast photoacoustic tomography reconstruction using deep learning neural networks

Bruno De Santi, Fazael Ayatollahi, Felix Lucka, Navchetan Awasthi, Ben Cox, Srirang Manohar

Author Affiliations +

Proceedings Volume PC12379, Photons Plus Ultrasound: Imaging and Sensing 2023; PC123793G (2023) https://doi.org/10.1117/12.2650604
Event: SPIE BiOS, 2023, San Francisco, California, United States

Conference Poster

Abstract

In photoacoustic tomography, the target object is illuminated by a short-pulsed light and multiple ultrasonic transducers are used to measure PA waves. Image reconstruction is needed to create a map of the initial acoustic pressure. In case of insufficient number of projections (views) around the object, the reconstructed image suffers from lower quality. We trained a CNN to improve the quality of less-view breast PA images, using the full-view reconstructions as ground-truth. The proposed network can reduce the acquisition time while preserving image quality.

Citation Download Citation

Bruno De Santi, Fazael Ayatollahi, Felix Lucka, Navchetan Awasthi, Ben Cox, and Srirang Manohar "Improving quality of less-view breast photoacoustic tomography reconstruction using deep learning neural networks", Proc. SPIE PC12379, Photons Plus Ultrasound: Imaging and Sensing 2023, PC123793G (27 March 2023); https://doi.org/10.1117/12.2650604

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