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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE access Ročník 10; s. 1
Hlavní autoři:	Duc, Nguyen Thanh, Oanh, Nguyen Thi, Thuy, Nguyen Thi, Triet, Tran Minh, Sang, Dinh Viet
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!