ColonFormer: An Efficient Transformer based Method for Colon Polyp Segmentation

Identifying polyps is challenging for automatic analysis of endoscopic images in computer-aided clinical support systems. Models based on convolutional networks (CNN), transformers, and their combinations have been proposed to segment polyps with promising results. However, those approaches have lim...

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Vydané v:	IEEE access Ročník 10; s. 1
Hlavní autori:	Duc, Nguyen Thanh, Oanh, Nguyen Thi, Thuy, Nguyen Thi, Triet, Tran Minh, Sang, Dinh Viet
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Benchmarks Coders Colon colonoscopy Computational modeling Computer architecture computer-aided diagnosis Convolutional neural networks Datasets Decoding deep learning encoder-decoder network Encoders-Decoders Feature extraction hierarchical multi-scale CNN Image segmentation Modelling Polyp segmentation Polyps Representations Semantic segmentation Semantics Structural hierarchy Support systems Transformers
ISSN:	2169-3536, 2169-3536
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