Attention-Guided deep atrous-residual U-Net architecture for automated gland segmentation in colon histopathology images

Attention-Guided deep atrous-residual U-Net architecture for automated gland segmentation in colon histopathology images

In digital pathology, gland segmentation plays a dominant part in the diagnosis and quantification of colon cancer. Thus, this paper presents a clinically relevant deep learning-based automated gland segmentation technique called Attention-Guided deep Atrous-Residual U-Net that aims to seize small a...

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Bibliographic Details
Main Authors: Manju Dabass, Sharda Vashisth, Rekha Vig
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Colon histopathology images
Automated gland segmentation
Deep learning
Residual learning
Attention mechanism
Multi-scale feature fusion
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914821002550

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http://www.sciencedirect.com/science/article/pii/S2352914821002550

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