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20182025
most citedReal-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning

405 citations · 449 across the 10 of their papers we have counts for

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7 papers · 1 filter

eess.IV2021

Exploring Deep Learning Methods for Real-Time Surgical Instrument Segmentation in Laparoscopy

Debesh Jha, Sharib Ali, Nikhil Kumar Tomar +4

Minimally invasive surgery is a surgical intervention used to examine the organs inside the abdomen and has been widely used due to its effectiveness over open surgery. Due to the…

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.IV2020

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…

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…

eess.IV202018 cited

DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation

Debesh Jha, Michael A. Riegler, Dag Johansen +2

Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a pop…

eess.IV2019

Kvasir-SEG: A Segmented Polyp Dataset

Debesh Jha, Pia H. Smedsrud, Michael A. Riegler +4

Pixel-wise image segmentation is a highly demanding task in medical-image analysis. In practice, it is difficult to find annotated medical images with corresponding segmentation ma…