SAMU-Net: A dual-stage polyp segmentation network with a custom attention-based U-Net and segment anything model for enhanced mask prediction

SAMU-Net: A dual-stage polyp segmentation network with a custom attention-based U-Net and segment anything model for enhanced mask prediction

Early detection of colorectal cancer through the proper segmentation of polyps in the colonoscopy images is crucial. Polyps' complex morphology and varied appearances are the greatest obstacles for the segmentation approaches. The paper introduces SAMU-Net, a novel deep learning-based dual-stag...

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Bibliographic Details
Main Authors: Radiful Islam, Rashik Shahriar Akash, Md Awlad Hossen Rony, Md Zahid Hasan
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Array
Online Access:http://www.sciencedirect.com/science/article/pii/S2590005624000365
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