A5055184717- Colorectal Cancer Screening and Detection
- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Gastrointestinal Bleeding Diagnosis and Treatment
- Context-Aware Activity Recognition Systems
- Pancreatic and Hepatic Oncology Research
- Mobile Health and mHealth Applications
- Gastric Cancer Management and Outcomes
- Human Pose and Action Recognition
- Advanced Neural Network Applications
- Southeast Asian Sociopolitical Studies
- Domain Adaptation and Few-Shot Learning
- South Asian Studies and Conflicts
- Handwritten Text Recognition Techniques
- COVID-19 diagnosis using AI
- Machine Learning and Data Classification
- Physical Activity and Health
- Gastrointestinal disorders and treatments
- Medical Image Segmentation Techniques
University of Oslo
2019-2025
Simula Research Laboratory
2025
Simula Metropolitan Center for Digital Engineering
2019-2021
Abstract Artificial intelligence is currently a hot topic in medicine. However, medical data often sparse and hard to obtain due legal restrictions lack of personnel for the cumbersome tedious process manually label training data. These constraints make it difficult develop systems automatic analysis, like detecting disease or other lesions. In this respect, article presents HyperKvasir , largest image video dataset gastrointestinal tract available today. The collected during real gastro-...
Abstract Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology. The potential lies in improving anomaly detection while reducing manual labour. Existing work demonstrates promising benefits AI-based computer-assisted diagnosis systems for VCE. They also show great improvements achieve even better results. Also, medical data often sparse and unavailable research community, qualified personnel rarely time tedious labelling...
In this paper, we present PMData: a dataset that combines traditional lifelogging data with sports-activity data. Our enables the development of novel analysis and machine-learning applications where, for instance, additional sports is used to predict analyze everyday developments, like person's weight sleep patterns; where lifelog in context athletes' performance. PMData input from Fitbit Versa 2 smartwatch wristbands, PMSys logging smartphone application, Google forms. Logging has been...
Artificial intelligence is currently a hot topic in medicine. The fact that medical data often sparse and hard to obtain due legal restrictions lack of personnel perform the cumbersome tedious labeling leads limitations for what would be possible achieve with automatic analysis. In this respect, article presents HyperKvasir which largest image video dataset gastrointestinal tract available today. collected during real gastro- colonoscopy examinations at Bærum Hospital Norway partly labeled...
Gastrointestinal (GI) endoscopy has been an active field of research motivated by the large number highly lethal GI cancers. Early cancer precursors are often missed during endoscopic surveillance. The high rate such abnormalities is thus a critical bottleneck. Lack attentiveness due to tiring procedures, and requirement training few contributing factors. An automatic disease classification system can help reduce risks flagging suspicious frames lesions. consists several multi-organ...
We introduce a weakly supervised segmentation approach that leverages class activation maps and the Segment Anything Model to generate high-quality masks using only classification data. A pre-trained classifier produces that, once thresholded, yield bounding boxes encapsulating regions of interest. These prompt SAM detailed masks, which are then refined by selecting best overlap with automatically generated from foundational model intersection over union metric. In polyp case study, our...
In this paper, we present PMData: a dataset that combines traditional lifelogging data with sports-activity data. Our enables the development of novel analysis and machine-learning applications where, for instance, additional sports is used to predict analyze everyday developments, like person's weight sleep patterns; where lifelog in context athletes' performance. \datasetname input from Fitbit Versa 2 smartwatch wristbands, PMSys logging smartphone application, Google forms. Logging has...
Artificial intelligence (AI) is predicted to have profound effects on the future of video capsule endoscopy (VCE) technology.The potential lies in improving anomaly detection while reducing manual labour. However, medical data often sparse andunavailable research community, and qualified personnel rarely time for tedious labelling work. In this respect, we present Kvasir-Capsule, a large VCE dataset collected from examinations at Hospitals Norway. Kvasir-Capsule consists 118 videos which can...