Classification of multilayered cancerous colorectal tissue using fiber-array diffuse reflectance spectroscopy and a multi-output neural network

Freija Geldof; Kaylee van Duren; Lynn-Jade Jong; Dinusha Veluponnar; Henricus Sterenborg; Behdad Dashtbozorg; Theo Ruers

doi:10.1117/12.2607758

9 March 2022 Classification of multilayered cancerous colorectal tissue using fiber-array diffuse reflectance spectroscopy and a multi-output neural network

Freija Geldof, Kaylee van Duren, Lynn-Jade Jong, Dinusha Veluponnar, Henricus Sterenborg, Behdad Dashtbozorg, Theo Ruers

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Proceedings Volume PC11949, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XX; PC119490C (2022) https://doi.org/10.1117/12.2607758
Event: SPIE BiOS, 2022, San Francisco, California, United States

Abstract

Diffuse reflectance spectroscopy (DRS) has already been successfully used for tissue discrimination during colorectal cancer surgery. In clinical practice, however, tissue often consists of several layers. Therefore, a novel multi-output convolutional neural network (CNN) was designed to classify multiple layers of colorectal cancer tissue simultaneously. DRS data was acquired with an array of six fibers with different fiber distances to sample at multiple depths. After training a 2D CNN with the DRS data as input, the first, second, and third tissue layers could be classified with mean accuracies of 0.90, 0.71, and 0.62, respectively.

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Freija Geldof, Kaylee van Duren, Lynn-Jade Jong, Dinusha Veluponnar, Henricus Sterenborg, Behdad Dashtbozorg, and Theo Ruers "Classification of multilayered cancerous colorectal tissue using fiber-array diffuse reflectance spectroscopy and a multi-output neural network", Proc. SPIE PC11949, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XX, PC119490C (9 March 2022); https://doi.org/10.1117/12.2607758

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KEYWORDS

Tissue optics

Tissues

Diffuse reflectance spectroscopy

Multilayers

Neural networks

Colorectal cancer

Surgery

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