Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma
Open Access
- 3 December 2018
- Vol. 68 (7), 1143-1145
- https://doi.org/10.1136/gutjnl-2018-317573
Abstract
Computer-aided diagnosis using deep learning (CAD-DL) may be an instrument to improve endoscopic assessment of Barrett’s oesophagus (BE) and early oesophageal adenocarcinoma (EAC). Based on still images from two databases, the diagnosis of EAC by CAD-DL reached sensitivities/specificities of 97%/88% (Augsburg data) and 92%/100% (Medical Image Computing and Computer-Assisted Intervention [MICCAI] data) for white light (WL) images and 94%/80% for narrow band images (NBI) (Augsburg data), respectively. Tumour margins delineated by experts into images were detected satisfactorily with a Dice coefficient (D) of 0.72. This could be a first step towards CAD-DL for BE assessment. If developed further, it could become a useful adjunctive tool for patient management.Keywords
Funding Information
- Cape/Alexander von Humboldt Foundation
- Deutsche Forschungsgemeinschaft
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