ConvSegNet: Automated Polyp Segmentation From Colonoscopy Using Context Feature Refinement With Multiple Convolutional Kernel Sizes

Colorectal cancer occurs in the rectal of humans, and early detection has been proved to reduce its mortality rate. Colonoscopy is the standard used in detecting the presence of polyps in the rectal, and accurate segmentation of the polyps from colonoscopy images often provides helpful information f...

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Bibliographic Details
Main Authors: Ayokunle Olalekan Ige, Nikhil Kumar Tomar, Felix Ola Aranuwa, Oluwafemi Oriola, Alaba O. Akingbesote, Mohd Halim Mohd Noor, Manuel Mazzara, Benjamin Segun Aribisala
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10043855/