23 citations · 98 across the 22 of their papers we have counts for
12 papers · 1 filter
A Dual Convolutional Neural Network Pipeline for Melanoma Diagnostics and Prognostics
Marie Bø-Sande, Edvin Benjaminsen, Neel Kanwal +5
Melanoma is a type of cancer that begins in the cells controlling the pigment of the skin, and it is often referred to as the most dangerous skin cancer. Diagnosing melanoma can be…
Balancing Privacy and Progress in Artificial Intelligence: Anonymization in Histopathology for Biomedical Research and Education
Neel Kanwal, Emiel A. M. Janssen, Kjersti Engan
The advancement of biomedical research heavily relies on access to large amounts of medical data. In the case of histopathology, Whole Slide Images (WSI) and clinicopathological in…
Towards a privacy-preserving distributed cloud service for preprocessing very large medical images
Yuandou Wang, Neel Kanwal, Kjersti Engan +2
Digitized histopathology glass slides, known as Whole Slide Images (WSIs), are often several gigapixels large and contain sensitive metadata information, which makes distributed pr…
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…
Self-supervised learning of a tailored Convolutional Auto Encoder for histopathological prostate grading
Zahra Tabatabaei, Adrian colomer, Kjersti Engan +2
According to GLOBOCAN 2020, prostate cancer is the second most common cancer in men worldwide and the fourth most prevalent cancer overall. For pathologists, grading prostate cance…
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation
Luca Tomasetti, Stine Hansen, Mahdieh Khanmohammadi +4
Precise ischemic lesion segmentation plays an essential role in improving diagnosis and treatment planning for ischemic stroke, one of the prevalent diseases with the highest morta…
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…
Deep Learning for Predicting Metastasis on Melanoma WSIs
Christopher Andreassen, Saul Fuster, Helga Hardardottir +2
Northern Europe has the second highest mortality rate of melanoma globally. In 2020, the mortality rate of melanoma rose to 1.9 per 100 000 habitants. Melanoma prognosis is based o…
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,…
CT Perfusion is All We Need: 4D CNN Segmentation of Penumbra and Core in Patients With Suspected Ischemic Stroke
Luca Tomasetti, Kjersti Engan, Liv Jorunn Høllesli +2
Precise and fast prediction methods for ischemic areas comprised of dead tissue, core, and salvageable tissue, penumbra, in acute ischemic stroke (AIS) patients are of significant…
Detection and Localization of Melanoma Skin Cancer in Histopathological Whole Slide Images
Neel Kanwal, Roger Amundsen, Helga Hardardottir +4
Melanoma diagnosed and treated in its early stages can increase the survival rate. A projected increase in skin cancer incidents and a dearth of dermatopathologists have emphasized…