Blar i Vitenskapelige publikasjoner (TN-IDE) på forfatter "Engan, Kjersti"
-
Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review
Khoraminia, Farbod; Fuster Navarro, Saul; Kanwal, Neel; Olislagers, Mitchell; Engan, Kjersti; Leenders, Geet J.L.H. Van; Stubbs, Andrew P; Akram, Farhan; Zuiverloon, Tahlita C.M. (Peer reviewed; Journal article, 2023)Bladder cancer (BC) diagnosis and prediction of prognosis are hindered by subjective pathological evaluation, which may cause misdiagnosis and under-/over-treatment. Computational pathology (CPATH) can identify clinical ... -
Automatic diagnostic tool for predicting cancer grade in bladder cancer patients using deep learning
Wetteland, Rune; Engan, Kjersti; Eftestøl, Trygve Christian; Kvikstad, Vebjørn; Janssen, Emiel; Tøssebro, Erlend; Lillesand, Melinda (Peer reviewed; Journal article, 2021-08)The most common type of bladder cancer is urothelial carcinoma, which is among the cancer types with the highest recurrence rate and lifetime treatment cost per patient. Diagnosed patients are stratified into risk groups, ... -
Automatic Estimation of Coronary Blood Flow Velocity Step 1 for Developing a Tool to Diagnose Patients With Micro-Vascular Angina Pectoris
Khanmohammadi, Mahdieh; Sæland, Charlotte; Engan, Kjersti; Eftestøl, Trygve Christian; Larsen, Alf Inge (Journal article; Peer reviewed, 2019-01)Aim: Our aim was to automatically estimate the blood velocity in coronary arteries using cine X-ray angiographic sequence. Estimating the coronary blood velocity is a key approach in investigating patients with angina ... -
Balancing privacy and progress in artificial intelligence : Anonymization in histopathology for biomedical research and education
Kanwal, Neel; Janssen, Emiel; Engan, Kjersti (Frontiers of Artificial Intelligence, Ethics and Multidisciplinary Applications;, Chapter, 2024)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 information are valuable for developing ... -
Classifying dementia using local binary patterns from different regions in magnetic resonance images
Oppedal, Ketil; Eftestøl, Trygve; Engan, Kjersti; Beyer, Mona K.; Aarsland, Dag (Journal article; Peer reviewed, 2015)Dementia is an evolving challenge in society, and no disease-modifying treatment exists. Diagnosis can be demanding and MR imaging may aid as a noninvasive method to increase prediction accuracy. We explored the use of 2D ... -
CT Perfusion is All We Need: 4D CNN Segmentation of Penumbra and Core in Patients With Suspected Acute Ischemic Stroke
Tomasetti, Luca; Engan, Kjersti; Høllesli, Liv Jorunn; Kurz, Kathinka Dæhli; Khanmohammadi, Mahdieh (Peer reviewed; Journal article, 2023)Stroke is the second leading cause of death worldwide, and around 87 % of strokes are ischemic strokes. Accurate and rapid prediction techniques for identifying ischemic regions, including dead tissue (core) and potentially ... -
Defining angular and radial positions and parameters for myocardial pixels in cardiac MR images
Engan, Kjersti; Woie, Leik; Eftestøl, Trygve (Journal article; Peer reviewed, 2014)In this work we aimed to automatically produce a measure for the angular and radial position of all pixels within the myocardium in CMR images, left ventricle, short axis view. A reference axis is chosen in an anatomically ... -
Detection and localization of melanoma skin cancer in histopathological whole slide images
Kanwal, Neel; Amundsen, Roger; Hardardottir, Helga; Tomasetti, Luca; Undersrud, Erling Sandøy; Janssen, Emiel; Engan, Kjersti (European Signal Processing Conference;, Chapter; Conference object, 2023)If melanoma is diagnosed and treated in its early stages can increase the survival rate. A projected increase in skin cancer incidents and a shortage of dermatopathologists have emphasized the need for computational pathology ... -
The devil is in the details: Whole Slide Image acquisition and processing for artifacts detection, color variation, and data augmentation: A review.
Kanwal, Neel; Pérez-Bueno, Fernando; Schmidt, Arne; Engan, Kjersti; Molina, Rafael (Peer reviewed; Journal article, 2022)Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis of different types of cancer. The preparation and digitization of histological tissues leads to the introduction of artifacts and ... -
Invasive cancerous area detection in non-muscle invasive bladder cancer whole slide images
Fuster Navarro, Saul; Khoraminia, Farbod; Kiraz, Umay; Kanwal, Neel; Kvikstad, Vebjørn; Eftestøl, Trygve Christian; Zuiverloon, Tahlita C M; Janssen, Emiel; Engan, Kjersti (Chapter, 2022)Bladder cancer patients’ stratification into risk groups relies on grade, stage and clinical factors. For non-muscle invasive bladder cancer, T1 tumours that invade the subepithelial tissue are high-risk lesions with a ... -
Machine learning algorithms vs. thresholding to segment ischemic regions in patients with acute ischemic stroke
Tomasetti, Luca; Høllesli, Liv Jorunn; Engan, Kjersti; Kurz, Kathinka Dæhli; Kurz, Martin Wilhelm; Khanmohammadi, Mahdieh (Peer reviewed; Journal article, 2021-07)Objective: Computed tomography (CT) scan is a fast and widely used modality for early assessment in patients with symptoms of a cerebral ischemic stroke. CT perfusion (CTP) is often added to the protocol and is used by ... -
Multi-input segmentation of damaged brain in acute ischemic stroke patients using slow fusion with skip connection
Tomasetti, Luca; Khanmohammadi, Mahdieh; Engan, Kjersti; Høllesli, Liv Jorunn; Kurz, Kathinka Dæhli (Peer reviewed; Journal article, 2022-03)Time is a fundamental factor during stroke treatments. A fast, automatic approach that segmentsthe ischemic regions helps treatment decisions. In clinical use today, a set of color-coded parametric maps generated from ... -
A Multiscale Approach for Whole-Slide Image Segmentation of five Tissue Classes in Urothelial Carcinoma Slides
Wetteland, Rune; Engan, Kjersti; Eftestøl, Trygve Christian; Janssen, Emiel; Kvikstad, Vebjørn (Peer reviewed; Journal article, 2020)In pathology labs worldwide, we see an increasing number of tissue samples that need to be assessed without the same increase in the number of pathologists. Computational pathology, where digital scans of histological ... -
NewbornTime - improved newborn care based on video and artificial intelligence - study protocol
Engan, Kjersti; Meinich-Bache, Øyvind; Brunner, Sara; Myklebust, Helge; Rong, Chunming; Garcia-Torres Fernandez, Jorge; Ersdal, Hege Langli; Johannessen, Anders; Pike, Hanne; Rettedal, Siren (Journal article, 2023)Background Approximately 3-8% of all newborns do not breathe spontaneously at birth, and require time critical resuscitation. Resuscitation guidelines are mostly based on best practice, and more research on newborn ... -
Probability mapping of scarred myocardium using texture and intensity features in CMR images
Kotu, Lasya Priya; Engan, Kjersti; Skretting, Karl; Måløy, Frode; Ørn, Stein; Woie, Leik; Eftestøl, Trygve (Journal article, 2013) -
Quantifying the effect of color processing on blood and damaged tissue detection in Whole Slide Images
Kanwal, Neel; Fuster Navarro, Saul; Khoraminia, Farbod; Zuiverloon, Tahlita C M; Chunming, Rong; Engan, Kjersti (Chapter, 2022)Histological tissue examination has been a longstanding practice for cancer diagnosis where pathologists identify the presence of tumors on glass slides. Slides acquired from laboratory routine may contain unintentional ... -
Semi-supervised tissue segmentation of histological images
Wetteland, Rune; Dalheim, Ove Nicolai; Kvikstad, Vebjørn; Janssen, Emiel; Engan, Kjersti (Peer reviewed; Journal article, 2020-09)Supervised learning of convolutional neural networks (CNN) used for image classification and segmentation has produced state-of-the art results, including in many medical image applications. In the medical field, making ... -
State transition modeling of complex monitored health data
Schulz, Jörn; Kvaløy, Jan Terje; Engan, Kjersti; Eftestøl, Trygve Christian; Jatosh, Samwel; Hussein, Kidanto; Ersdal, Hege Langli (Peer reviewed; Journal article, 2019)This article considers the analysis of complex monitored health data, where often one or several signals are reflecting the current health status that can be represented by a finite number of states, in addition to a set ... -
Towards using Thermal Cameras in Birth Detection
Garcia-Torres Fernandez, Jorge; Meinich-Bache, Øyvind; Sara, Brunner; Johannessen, Anders; Rettedal, Siren; Engan, Kjersti (Chapter, 2022)In recent years, thermal imaging has been used in numerous applications due to its ability to capture and visualize the thermal radiation emitted by objects. Thermal cameras can be employed as non-invasive systems for ... -
Vision transformers for small histological datasets learned through knowledge distillation
Kanwal, Neel; Eftestøl, Trygve Christian; Khoraminia, Farbod; Zuiverloon, Tahlita C M; Engan, Kjersti (Chapter, 2023)Computational Pathology (CPATH) systems have the potential to automate diagnostic tasks. However, the artifacts on the digitized histological glass slides, known as Whole Slide Images (WSIs), may hamper the overall performance ...