23 citations · 44 across the 9 of their papers we have counts for
7 papers · 1 filter
Leveraging multi-view data without annotations for prostate MRI segmentation: A contrastive approach
Tim Nikolass Lindeijer, Tord Martin Ytredal, Trygve Eftestøl +4
An accurate prostate delineation and volume characterization can support the clinical assessment of prostate cancer. A large amount of automatic prostate segmentation tools conside…
On undesired emergent behaviors in compound prostate cancer detection systems
Erlend Sortland Rolfsnes, Philip Thangngat, Trygve Eftestøl +4
Artificial intelligence systems show promise to aid in the di- agnostic pathway of prostate cancer (PC), by supporting radiologists in interpreting magnetic resonance images (MRI)…
Out-of-distribution multi-view auto-encoders for prostate cancer lesion detection
Alvaro Fernandez-Quilez, Linas Vidziunas, Ørjan Kløvfjell Thoresen +3
Traditional deep learning (DL) approaches based on supervised learning paradigms require large amounts of annotated data that are rarely available in the medical domain. Unsupervis…
Vision Transformers for Small Histological Datasets Learned through Knowledge Distillation
Neel Kanwal, Trygve Eftestol, Farbod Khoraminia +2
Computational Pathology (CPATH) systems have the potential to automate diagnostic tasks. However, the artifacts on the digitized histological glass slides, known as Whole Slide Ima…
Object Detection During Newborn Resuscitation Activities
Øyvind Meinich-Bache, Kjersti Engan, Ivar Austvoll +5
Birth asphyxia is a major newborn mortality problem in low-resource countries. International guideline provides treatment recommendations; however, the importance and effect of the…
Activity Recognition From Newborn Resuscitation Videos
Øyvind Meinich-Bache, Simon Lennart Austnes, Kjersti Engan +6
Objective: Birth asphyxia is one of the leading causes of neonatal deaths. A key for survival is performing immediate and continuous quality newborn resuscitation. A dataset of rec…
Active Learning Based Domain Adaptation for Tissue Segmentation of Histopathological Images
Saul Fuster, Farbod Khoraminia, Trygve Eftestøl +2
Accurate segmentation of tissue in histopathological images can be very beneficial for defining regions of interest (ROI) for streamline of diagnostic and prognostic tasks. Still,…