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
6 papers · 1 filter
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…
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…
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…