Classification of Polyps in Endoscopic Images Using Self-Supervised Structured Learning

Classification of Polyps in Endoscopic Images Using Self-Supervised Structured Learning

This study uses a two-stage learning computer-aided diagnosis (CAD) scheme that has a convolutional neural network(CNN) with self-supervised learning(SSL) to classify polyps as either a hyperplastic polyp (HP) or a Tubular Adenoma (TA). The proposed model uses look-into-object (LIO) and contrastive...

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Bibliographic Details
Main Authors: Qi-Xian Huang, Guo-Shiang Lin, Hung-Min Sun
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Computer-aided diagnosis
self-supervised learning
SimCLR
Polyp classification
look-into-object
Online Access:https://ieeexplore.ieee.org/document/10128702/

Internet

https://ieeexplore.ieee.org/document/10128702/

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