BNCNN based diffuse optical imaging

Nazish Murad; Min-Chun Pan; Ya-Fen Hsu

doi:10.1117/12.2609193

2 March 2022 BNCNN based diffuse optical imaging

Nazish Murad, Min-Chun Pan, Ya-Fen Hsu

Proceedings Volume 11952, Multimodal Biomedical Imaging XVII; 1195208 (2022) https://doi.org/10.1117/12.2609193
Event: SPIE BiOS, 2022, San Francisco, California, United States

Conference Poster

Abstract

We proposed and implemented a deep learning scheme using convolution neural networks (CNNs) with batch normalization (BNCNN) to construct a sensor-image DOI computation model with the aim of reconstructing tissue optical-property images as well as identifying and localizing breast tumors. A non-iterative learning reconstruction method was developed to recover optical properties, focusing on one-dimensional convolution layers followed by dense layers. Besides simulated data for model training, validation and testing, for the comparison of model performance, measurement data sets were employed to test on the same trained network which results outperform Tikhonov regularization method and other artificial neural networks as well.

Conference Presentation

Citation Download Citation

Nazish Murad, Min-Chun Pan, and Ya-Fen Hsu "BNCNN based diffuse optical imaging", Proc. SPIE 11952, Multimodal Biomedical Imaging XVII, 1195208 (2 March 2022); https://doi.org/10.1117/12.2609193

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