PRAPNet: A Parallel Residual Atrous Pyramid Network for Polyp Segmentation

PRAPNet: A Parallel Residual Atrous Pyramid Network for Polyp Segmentation

In a colonoscopy, accurate computer-aided polyp detection and segmentation can help endoscopists to remove abnormal tissue. This reduces the chance of polyps developing into cancer, which is of great importance. In this paper, we propose a neural network (parallel residual atrous pyramid network or...

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Bibliographic Details
Main Authors: Jubao Han, Chao Xu, Ziheng An, Kai Qian, Wei Tan, Dou Wang, Qianqian Fang
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Sensors
Subjects:
medical image analysis
semantic segmentation
colonoscopy
polyp segmentation
deep learning
health informatics
Online Access:https://www.mdpi.com/1424-8220/22/13/4658

Internet

https://www.mdpi.com/1424-8220/22/13/4658

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