activity
20202022
most citedAssessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge

19 citations · 39 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2022

PolypConnect: Image inpainting for generating realistic gastrointestinal tract images with polyps

Jan Andre Fagereng, Vajira Thambawita, Andrea M. Storås +4

Early identification of a polyp in the lower gastrointestinal (GI) tract can lead to prevention of life-threatening colorectal cancer. Developing computer-aided diagnosis (CAD) sys…

eess.IV20223 cited

Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations

Steven Hicks, Andrea Storås, Michael Riegler +6

Deep learning has in recent years achieved immense success in all areas of computer vision and has the potential of assisting medical doctors in analyzing visual content for diseas…

cs.CV202219 cited

Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge

Sharib Ali, Noha Ghatwary, Debesh Jha +29

Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, location, and surface largely affect identification, localisation, and charac…

eess.IV20212 cited

NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy

Debesh Jha, Nikhil Kumar Tomar, Sharib Ali +5

Deep learning in gastrointestinal endoscopy can assist to improve clinical performance and be helpful to assess lesions more accurately. To this extent, semantic segmentation metho…

eess.IV202015 cited

Medico Multimedia Task at MediaEval 2020: Automatic Polyp Segmentation

Debesh Jha, Steven A. Hicks, Krister Emanuelsen +5

Colorectal cancer is the third most common cause of cancer worldwide. According to Global cancer statistics 2018, the incidence of colorectal cancer is increasing in both developin…