DE-ColonSegNet: An Improved version of ColonSegNet with dual encoder for accurate real-time Polyp segmentation in colonoscopy-Reference-Cited by-同舟云学术

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DE-ColonSegNet: An Improved version of ColonSegNet with dual encoder for accurate real-time Polyp segmentation in colonoscopy

Published:2023-12-27 Issue: Volume: Page:1-5
ISSN:
Container-title:2023 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI)
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Author:

Nile Abdelrhman W.¹,Elsayed Fady A.¹,Mohamed Mohamed A.¹,Amer Ayman²,ELGohary Rania¹,Hafez Mohamed³,Deif Mohanad A.¹

Affiliation:

1. College of Information Technology, Misr University for Science and Technology (MUST), 6th of October city,Department of Artificial Intelligence,Giza,Egypt,12566

2. Zarqa University,Faculty of Engineering,Zarqa,Jordan

3. FEQS INTI-IU-University,Faculty of Engineering,Nilai,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10590066/10590003/10590125.pdf?arnumber=10590125

Reference26 articles.

1. Cancer statistics, 2022

2. A New Feature Selection Method Based on Hybrid Approach for Colorectal Cancer Histology Classification

3. ResUNet++: An Advanced Architecture for Medical Image Segmentation;Jha;arXiv,24, 2019

4. René G. Holzheimer & J. A. Mannick(Eds):Surgical treatment. Evidence-based and problem-oriented W. Zuckschwerdt Verlag, München, Bern, Wien, New York, 2001.(843 pages). ISBN 3-88603-714-2

5. ACG Clinical Guidelines: Colorectal Cancer Screening 2021

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