179 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of StavangerNO16 papers
- Karolinska InstitutetSE4 papers
- Science for Life LaboratorySE3 papers
- Griffith UniversityAU2 papers
- Laerdal (Norway)NO2 papers
- Medical University of LodzPL2 papers
- Synapse (Spain)ES2 papers
- Universitat Politècnica de ValènciaES2 papers
- University of BergenNO2 papers
- Aarhus UniversityDK1 paper
- Aarhus University HospitalDK1 paper
- Aichi Medical UniversityJP1 paper
17 papers
Clinical Pathways Matter for Multimodal Deep Learning in Early Alzheimers Disease Detection
Yao Lu, Solveig Kristina Hammonds, Alvaro Fernandez-Quilez
Identifying individuals at risk of Alzheimer's disease (AD), particularly in the preclinical and early stages, remains challenging. Although deep learning approaches based on struc…
Validation of Diagnostic Artificial Intelligence Models for Prostate Pathology in a Middle Eastern Cohort
Peshawa J. Muhammad Ali, Navin Vincent, Saman S. Abdulla +8
Background: Artificial intelligence (AI) is improving the efficiency and accuracy of cancer diagnostics. The performance of pathology AI systems has been almost exclusively evaluat…
Artificial Intelligence-Assisted Prostate Cancer Diagnosis for Reduced Use of Immunohistochemistry
Anders Blilie, Nita Mulliqi, Xiaoyi Ji +13
Prostate cancer diagnosis heavily relies on histopathological evaluation, which is subject to variability. While immunohistochemical staining (IHC) assists in distinguishing benign…
Foundation Models -- A Panacea for Artificial Intelligence in Pathology?
Nita Mulliqi, Anders Blilie, Xiaoyi Ji +28
The role of artificial intelligence (AI) in pathology has evolved from aiding diagnostics to uncovering predictive morphological patterns in whole slide images (WSIs). Recently, fo…
Two-Stream Thermal Imaging Fusion for Enhanced Time of Birth Detection in Neonatal Care
Jorge García-Torres, Øyvind Meinich-Bache, Sara Brunner +3
Around 10% of newborns require some help to initiate breathing, and 5\% need ventilation assistance. Accurate Time of Birth (ToB) documentation is essential for optimizing neonatal…
Advancing Newborn Care: Precise Birth Time Detection Using AI-Driven Thermal Imaging with Adaptive Normalization
Jorge García-Torres, Øyvind Meinich-Bache, Anders Johannessen +3
Around 5-10\% of newborns need assistance to start breathing. Currently, there is a lack of evidence-based research, objective data collection, and opportunities for learning from…
Boundary conditions for SPH through energy conservation
Jose Luis Cercos-Pita, Daniel Duque, Pablo Eleazar Merino-Alonso +1
Dealing with boundary conditions in Smoothed Particle Hydrodynamics (SPH) poses significant difficulties, indeed being one of the SPHERIC Grand Challenges. In particular, wall boun…
Self-Contrastive Weakly Supervised Learning Framework for Prognostic Prediction Using Whole Slide Images
Saul Fuster, Farbod Khoraminia, Julio Silva-Rodríguez +7
We present a pioneering investigation into the application of deep learning techniques to analyze histopathological images for addressing the substantial challenge of automated pro…
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…
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…
Challenging mitosis detection algorithms: Global labels allow centroid localization
Claudio Fernandez-Martín, Umay Kiraz, Julio Silva-Rodríguez +3
Mitotic activity is a crucial proliferation biomarker for the diagnosis and prognosis of different types of cancers. Nevertheless, mitosis counting is a cumbersome process for path…
Multi-input segmentation of damaged brain in acute ischemic stroke patients using slow fusion with skip connection
Luca Tomasetti, Mahdieh Khanmohammadi, Kjersti Engan +2
Time is a fundamental factor during stroke treatments. A fast, automatic approach that segments the ischemic regions helps treatment decisions. In clinical use today, a set of colo…
CNN Based Segmentation of Infarcted Regions in Acute Cerebral Stroke Patients From Computed Tomography Perfusion Imaging
Luca Tomasetti, Kjersti Engan, Mahdieh Khanmohammadi +1
More than 13 million people suffer from ischemic cerebral stroke worldwide each year. Thrombolytic treatment can reduce brain damage but has a narrow treatment window. Computed Tom…
Improving prostate whole gland segmentation in t2-weighted MRI with synthetically generated data
Alvaro Fernandez-Quilez, Steinar Valle Larsen, Morten Goodwin +3
Whole gland (WG) segmentation of the prostate plays a crucial role in detection, staging and treatment planning of prostate cancer (PCa). Despite promise shown by deep learning (DL…
The reliability of a deep learning model in clinical out-of-distribution MRI data: a multicohort study
Gustav Mårtensson, Daniel Ferreira, Tobias Granberg +22
Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in…
Multiscale Deep Neural Networks for Multiclass Tissue Classification of Histological Whole-Slide Images
Rune Wetteland, Kjersti Engan, Trygve Eftestøl +2
Correct treatment of urothelial carcinoma patients is dependent on accurate grading and staging of the cancer tumour. This is determined manually by a pathologist by examining the…