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EndoUDA: A modality independent segmentation approach for endoscopy
  imaging

EndoUDA: A modality independent segmentation approach for endoscopy imaging

12 July 2021
Numan Celik
Sharib Ali
Soumya Gupta
B. Braden
J. Rittscher
ArXiv (abs)PDFHTML

Papers citing "EndoUDA: A modality independent segmentation approach for endoscopy imaging"

3 / 3 papers shown
Title
Frontiers in Intelligent Colonoscopy
Frontiers in Intelligent Colonoscopy
Ge-Peng Ji
Jingyi Liu
Peng Xu
Nick Barnes
Fahad Shahbaz Khan
Salman Khan
Deng-Ping Fan
122
5
0
22 Oct 2024
SUPRA: Superpixel Guided Loss for Improved Multi-modal Segmentation in
  Endoscopy
SUPRA: Superpixel Guided Loss for Improved Multi-modal Segmentation in Endoscopy
Rafael Martinez Garcia Peña
Mansoor Ali Teevno
Gilberto Ochoa-Ruiz
Sharib Ali
74
3
0
09 Nov 2022
Assessing generalisability of deep learning-based polyp detection and
  segmentation methods through a computer vision challenge
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Sharib Ali
N. Ghatwary
Debesh Jha
Ece Isik Polat
Gorkem Polat
...
Dominique Lamarque
R. Cannizzaro
S. Realdon
Thomas de Lange
J. East
123
65
0
24 Feb 2022
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