Computer-aided diagnosis of laryngeal cancer via deep learning based on laryngoscopic images

2019150 citationsJournal Articlegold Open Access

Authors

Hao Xiong · Sun Yat-sen University

Peiliang Lin · Sun Yat-sen University

Jin-Gang Yu · South China University of Technology

Jin Ye · Sun Yat-sen University

Lichao Xiao · South China University of Technology

Tao Yuan · Peking University Shenzhen Hospital

Zebin Jiang

Abstract

The DCNN has high sensitivity and specificity for automated detection of LCA and PRELCA from BLT and NORM in laryngoscopic images. This novel and effective approach facilitates earlier diagnosis of early LCA, resulting in improved clinical outcomes and reducing the burden of endoscopists.

Topics & Keywords

Radiomics and Machine Learning in Medical Imaging Head and Neck Cancer Studies Brain Tumor Detection and Classification

UN Sustainable Development Goals

Good health and well-being

Publication Details

Published in: EBioMedicine

Volume 48, pp. 92-99

DOI: 10.1016/j.ebiom.2019.08.075

Field-Weighted Citation Impact: 8.71