SwinCup: Cascaded swin transformer for histopathological structures segmentation in colorectal cancer

Usama Zidan; Mohamed Medhat Gaber; Mohammed M. Abdelsamea

doi:10.1016/j.eswa.2022.119452

SwinCup: Cascaded swin transformer for histopathological structures segmentation in colorectal cancer

Usama Zidan, Mohamed Medhat Gaber, Mohammed M. Abdelsamea^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

35 Citations (SciVal)

Original language	English
Article number	119452
Journal	Expert Systems with Applications
Volume	216
DOIs	https://doi.org/10.1016/j.eswa.2022.119452
Publication status	Published (VoR) - 6 Jan 2023

Keywords

Deep learning
Gland segmentation
Histology image analysis
Self-supervision
Transformers

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10.1016/j.eswa.2022.119452

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title = "SwinCup: Cascaded swin transformer for histopathological structures segmentation in colorectal cancer",

keywords = "Deep learning, Gland segmentation, Histology image analysis, Self-supervision, Transformers",

author = "Usama Zidan and Gaber, {Mohamed Medhat} and Abdelsamea, {Mohammed M.}",

note = "Publisher Copyright: {\textcopyright} 2022 The Author(s)",

year = "2023",

month = jan,

day = "6",

doi = "10.1016/j.eswa.2022.119452",

language = "English",

volume = "216",

journal = "Expert Systems with Applications",

issn = "0957-4174",

publisher = "Elsevier",

}

TY - JOUR

T1 - SwinCup

T2 - Cascaded swin transformer for histopathological structures segmentation in colorectal cancer

AU - Zidan, Usama

AU - Gaber, Mohamed Medhat

AU - Abdelsamea, Mohammed M.

PY - 2023/1/6

Y1 - 2023/1/6

KW - Deep learning

KW - Gland segmentation

KW - Histology image analysis

KW - Self-supervision

KW - Transformers

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U2 - 10.1016/j.eswa.2022.119452

DO - 10.1016/j.eswa.2022.119452

M3 - Article

AN - SCOPUS:85145966256

SN - 0957-4174

VL - 216

JO - Expert Systems with Applications

JF - Expert Systems with Applications

M1 - 119452

ER -

SwinCup: Cascaded swin transformer for histopathological structures segmentation in colorectal cancer

Keywords

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