163 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of GothenburgSE8 papers
- Simula Metropolitan Center for Digital EngineeringNO3 papers
- Chalmers University of TechnologySE2 papers
- Harvard UniversityUS2 papers
- Lindholmen Science ParkSE2 papers
- Massachusetts General HospitalUS2 papers
- OsloMet – Oslo Metropolitan UniversityNO2 papers
- Oslo University HospitalNO2 papers
- UiT The Arctic University of NorwayNO2 papers
- Alexandria UniversityEG1 paper
- Amsterdam University Medical CentersNL1 paper
- Antaros Medical (Sweden)SE1 paper
14 papers
A method for supervoxel-wise association studies of age and other non-imaging variables from coronary computed tomography angiograms
Johan Öfverstedt, Elin Lundström, Göran Bergström +2
The study of associations between an individual's age and imaging and non-imaging data is an active research area that attempts to aid understanding of the effects and patterns of…
Proxy Design: A Method for Involving Proxy Users to Speak on Behalf of Vulnerable or Unreachable Users in Co-Design
Anna Sigridur Islind, Johan Lundin, Katerina Cerna +3
Designing digital artifacts is not a linear, straightforward process. This is particularly true when applying a user-centered design approach, or co-design, with users who are unab…
GAN-based generative modelling for dermatological applications -- comparative study
Sandra Carrasco Limeros, Sylwia Majchrowska, Mohamad Khir Zoubi +4
The lack of sufficiently large open medical databases is one of the biggest challenges in AI-powered healthcare. Synthetic data created using Generative Adversarial Networks (GANs)…
The (de)biasing effect of GAN-based augmentation methods on skin lesion images
Agnieszka Mikołajczyk, Sylwia Majchrowska, Sandra Carrasco Limeros
New medical datasets are now more open to the public, allowing for better and more extensive research. Although prepared with the utmost care, new datasets might still be a source…
Preoperative brain tumor imaging: models and software for segmentation and standardized reporting
D. Bouget, A. Pedersen, A. S. Jakola +27
For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the l…
A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation
Debesh Jha, Pia H. Smedsrud, Dag Johansen +4
Colonoscopy is considered the gold standard for detection of colorectal cancer and its precursors. Existing examination methods are, however, hampered by high overall miss-rate, an…
SinGAN-Seg: Synthetic training data generation for medical image segmentation
Vajira Thambawita, Pegah Salehi, Sajad Amouei Sheshkal +6
Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Artificial…
A multi-centre polyp detection and segmentation dataset for generalisability assessment
Sharib Ali, Debesh Jha, Noha Ghatwary +12
Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst most polyps are benign, the polyp's number, size and surface structure are linked to the ri…
Robust Machine Learning in Critical Care -- Software Engineering and Medical Perspectives
Miroslaw Staron, Helena Odenstedt Hergés, Silvana Naredi +4
Using machine learning in clinical practice poses hard requirements on explainability, reliability, replicability and robustness of these systems. Therefore, developing reliable so…
Extracting quantitative biological information from brightfield cell images using deep learning
Saga Helgadottir, Benjamin Midtvedt, Jesús Pineda +5
Quantitative analysis of cell structures is essential for biomedical and pharmaceutical research. The standard imaging approach relies on fluorescence microscopy, where cell struct…
Brain volume: An important determinant of functional outcome after acute ischemic stroke
Markus D. Schirmer, Kathleen L. Donahue, Marco J. Nardin +38
Objective: To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS). Methods: We analyzed cross-sectional data of the multi-site, i…
Natural Language Processing with Deep Learning for Medical Adverse Event Detection from Free-Text Medical Narratives: A Case Study of Detecting Total Hip Replacement Dislocation
Alireza Borjali, Martin Magneli, David Shin +3
Accurate and timely detection of medical adverse events (AEs) from free-text medical narratives is challenging. Natural language processing (NLP) with deep learning has already sho…
Crossing points in survival analysis sensitively depend on system conditions
Thomas McAndrew, Bjorn Redfors, Yiran Zhang +4
Crossing survival curves complicate how we interpret results from a clinical trial's primary endpoint. We find the function to determine a crossing point's location depends exponen…
Magnetoencephalography based on high-Tc superconductivity: a closer look into the brain?
F. Öisjöen, J. F. Schneiderman, G. A. Figueras +5
Magnetoencephalography (MEG) enables the study of brain activity by recording the magnetic fields generated by neural currents and has become an important technique for neuroscient…