405 citations · 440 across the 7 of their papers we have counts for
9 papers
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…
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…
LightLayers: Parameter Efficient Dense and Convolutional Layers for Image Classification
Debesh Jha, Anis Yazidi, Michael A. Riegler +3
Deep Neural Networks (DNNs) have become the de-facto standard in computer vision, as well as in many other pattern recognition tasks. A key drawback of DNNs is that the training ph…
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…
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…
Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning
Debesh Jha, Sharib Ali, Nikhil Kumar Tomar +5
Computer-aided detection, localisation, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and…
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…
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…
A Survey of Automatic Methods for Nutritional Assessment
Lars Brenna, Håvard D. Johansen, Dag Johansen
Nutritional assessment is key in order to make decisions about the nature and cause of nutrition related health issues that affect an individual. The systematic process of collecti…