Automatic classification of esophageal lesions in endoscopic images using a convolutional neural network | Zendy

Gaoshuang Liu | Zendy; Jie Hua | Zendy; Zhan Wu | Zendy; Tianfang Meng | Zendy; Mengxue Sun | Zendy; Pei-Yun Huang | Zendy; Xiaopu He | Zendy; Weihao Sun | Zendy; Xueliang Li | Zendy; Chen Yang | Zendy

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Automatic classification of esophageal lesions in endoscopic images using a convolutional neural network

Author(s) -

Gaoshuang Liu,

Jie Hua,

Zhan Wu,

Tianfang Meng,

Mengxue Sun,

Pei-Yun Huang,

Xiaopu He,

Weihao Sun,

Xueliang Li,

Chen Yang

Publication year - 2020

Publication title -

annals of translational medicine

Language(s) - English

Resource type - Journals

eISSN - 2305-5847

pISSN - 2305-5839

DOI - 10.21037/atm.2020.03.24

Subject(s) - artificial intelligence , convolutional neural network , pattern recognition (psychology) , support vector machine , computer science , local binary patterns , histogram of oriented gradients , deep learning , esophageal cancer , histogram , cancer , image (mathematics) , medicine

The CNN system, with 2 streams, demonstrated high sensitivity and specificity with the endoscopic images. It obtained better detection performance than the currently used methods based on the same datasets and has great application prospects in assisting endoscopists to distinguish esophageal lesion subclasses.

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