Deep features using convolutional neural network for early stage cancer detection

Sawon Pratiher; Shubhobrata Bhattacharya; Sabyasachi Mukhopadhyay; Nirmalya Ghosh; Gautham Pasupuleti; Prasanta K. Panigrahi

doi:10.1117/12.2300024

24 May 2018 Deep features using convolutional neural network for early stage cancer detection

Sawon Pratiher, Shubhobrata Bhattacharya, Sabyasachi Mukhopadhyay, Nirmalya Ghosh, Gautham Pasupuleti, Prasanta K. Panigrahi

Author Affiliations +

Proceedings Volume 10679, Optics, Photonics, and Digital Technologies for Imaging Applications V; 1067902 (2018) https://doi.org/10.1117/12.2300024
Event: SPIE Photonics Europe, 2018, Strasbourg, France

Abstract

In this contribution, we have done exploratory experiments using deep learning framework to classify elastic scattering spectra of biological tissues into normal and cancerous ones. An analytical assessment highlighting the superiority of convolutional neural network (CNN) extracted deep features over classical hand crafted biomarkers is discussed. The proposed method employs elastic scattering spectra of the tissues as input to CNN and thereby, averting the requirement of domain experts for extraction of diagnostic feature descriptors. Experimental results are discussed in detail.

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Sawon Pratiher, Shubhobrata Bhattacharya, Sabyasachi Mukhopadhyay, Nirmalya Ghosh, Gautham Pasupuleti, and Prasanta K. Panigrahi "Deep features using convolutional neural network for early stage cancer detection", Proc. SPIE 10679, Optics, Photonics, and Digital Technologies for Imaging Applications V, 1067902 (24 May 2018); https://doi.org/10.1117/12.2300024

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