19 citations · 24 across the 5 of their papers we have counts for
6 papers
TGANet: Text-guided attention for improved polyp segmentation
Nikhil Kumar Tomar, Debesh Jha, Ulas Bagci +1
Colonoscopy is a gold standard procedure but is highly operator-dependent. Automated polyp segmentation, a precancerous precursor, can minimize missed rates and timely treatment of…
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…
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…
Automatic Polyp Segmentation using Fully Convolutional Neural Network
Nikhil Kumar Tomar
Colorectal cancer is one of fatal cancer worldwide. Colonoscopy is the standard treatment for examination, localization, and removal of colorectal polyps. However, it has been show…
Automatic Polyp Segmentation using U-Net-ResNet50
Saruar Alam, Nikhil Kumar Tomar, Aarati Thakur +2
Polyps are the predecessors to colorectal cancer which is considered as one of the leading causes of cancer-related deaths worldwide. Colonoscopy is the standard procedure for the…
DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation
Nikhil Kumar Tomar, Debesh Jha, Sharib Ali +4
Colonoscopy is the gold standard for examination and detection of colorectal polyps. Localization and delineation of polyps can play a vital role in treatment (e.g., surgical plann…