24 May 2018 Deep features using convolutional neural network for early stage cancer detection
Author Affiliations +
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.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sawon Pratiher, Sawon Pratiher, Shubhobrata Bhattacharya, Shubhobrata Bhattacharya, Sabyasachi Mukhopadhyay, Sabyasachi Mukhopadhyay, Nirmalya Ghosh, Nirmalya Ghosh, Gautham Pasupuleti, Gautham Pasupuleti, Prasanta K. Panigrahi, 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); doi: 10.1117/12.2300024; https://doi.org/10.1117/12.2300024

Back to Top