405 citations · 879 across the 43 of their papers we have counts for
17 papers · 1 filter
GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection
Debesh Jha, Vanshali Sharma, Neethi Dasu +8
Integrating real-time artificial intelligence (AI) systems in clinical practices faces challenges such as scalability and acceptance. These challenges include data availability, bi…
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges
Debesh Jha, Vanshali Sharma, Debapriya Banik +30
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps durin…
Mask-conditioned latent diffusion for generating gastrointestinal polyp images
Roman Macháček, Leila Mozaffari, Zahra Sepasdar +4
In order to take advantage of AI solutions in endoscopy diagnostics, we must overcome the issue of limited annotations. These limitations are caused by the high privacy concerns in…
MLC at HECKTOR 2022: The Effect and Importance of Training Data when Analyzing Cases of Head and Neck Tumors using Machine Learning
Vajira Thambawita, Andrea M. Storås, Steven A. Hicks +2
Head and neck cancers are the fifth most common cancer worldwide, and recently, analysis of Positron Emission Tomography (PET) and Computed Tomography (CT) images has been proposed…
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…
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…
2020 CATARACTS Semantic Segmentation Challenge
Imanol Luengo, Maria Grammatikopoulou, Rahim Mohammadi +37
Surgical scene segmentation is essential for anatomy and instrument localization which can be further used to assess tissue-instrument interactions during a surgical procedure. In…
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…
DivergentNets: Medical Image Segmentation by Network Ensemble
Vajira Thambawita, Steven A. Hicks, Pål Halvorsen +1
Detection of colon polyps has become a trending topic in the intersecting fields of machine learning and gastrointestinal endoscopy. The focus has mainly been on per-frame classifi…
A multi-centre polyp detection and segmentation dataset for generalisability assessment
Sharib Ali, Debesh Jha, Noha Ghatwary +12
Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst most polyps are benign, the polyp's number, size and surface structure are linked to the ri…
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…
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…
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…
ResUNet++: An Advanced Architecture for Medical Image Segmentation
Debesh Jha, Pia H. Smedsrud, Michael A. Riegler +4
Accurate computer-aided polyp detection and segmentation during colonoscopy examinations can help endoscopists resect abnormal tissue and thereby decrease chances of polyps growing…
Stacked dense optical flows and dropout layers to predict sperm motility and morphology
Vajira Thambawita, Pål Halvorsen, Hugo Hammer +2
In this paper, we analyse two deep learning methods to predict sperm motility and sperm morphology from sperm videos. We use two different inputs: stacked pure frames of videos and…