Professor of Medical Image Analysis
Full list of publications found on my Google Scholar profile.
Semantic similarity metrics for learned image registration
S Czolbe, O Krause, A Feragen
MIDL 2021
[Paper] [bibtex] [Video]
Is segmentation uncertainty useful?
S Czolbe, K Arnavaz, O Krause, A Feragen
Information Processing in Medical Imaging 2021
[Paper] [preprint] [Video] [bibtex]
Q-space trajectory imaging with positivity constraints (QTI+)
M Herberthson, D Boito, TD Haije, A Feragen, CF Westin, E Özarslan
NeuroImage 238, 2021
[Paper]
Spot the Difference: Topological Anomaly Detection via Geometric Alignment
S Czolbe, A Feragen, O Krause
Under review, 2021
[Preprint]
Graph2Graph Learning with Conditional Autoregressive Models
G Wang, FB Lauze, A Feragen
Under review, 2021
[Preprint]
Semi-supervised, Topology-Aware Segmentation of Tubular Structures from Live Imaging 3D Microscopy
K Arnavaz, O Krause, JM Krivokapic, S Heilmann, JA Bærentzen, P Nyeng, A Feragen
[Preprint]
Assessing Bias in Medical AI
M Ganz, SH Holm, A Feragen
Interpretable Machine Learning in Healthcare, workshop at ICML 2021
[Paper] [bibtex]
Graph-Valued Regression: Prediction of unlabelled networks in a Non-Euclidean Graph-Space
A Calissano, A Feragen, S Vantini
In Preparation, 2020
[preprint]
Enforcing necessary non-negativity constraints for common diffusion MRI models using sum of squares programming
TD Haije, E Özarslan, A Feragen
NeuroImage, 2020
[Paper] [bibtex]
Populations of Unlabeled Networks: Graph Space Geometry and Geodesic Principal Components
A Calissano, A Feragen, S Vantini
In Review
[Preprint] [bibtex]
Optimized Response Function Estimation for Spherical Deconvolution
T Dela Haije, A Feragen
Computational Diffusion MRI. Mathematics and Visualization, Springer.
Proceedings of CDMRI Workshop at MICCAI 2019
[Paper]
Conceptual parallels between stochasticgeometry and diffusion-weighted MRI
T Dela Haije, A Feragen
Proceedings of Dagstuhl Seminar on Visualization and Processing of Anisotropy in Imaging, Geometry, and Astronomy 2018
[PDF]
Bayesian Active Learning for Maximal Information Gain on Model Parameters
K Arnavaz, A Feragen, O Krause, M Loog
International Conference on Pattern Recognition (ICPR) 2020
[PDF}
DeepSim: Semantic similarity metrics for learned image registration
S Czolbe, O Krause, A Feragen
Medical Imaging meets NeurIPS (MedNeurIPS) workshop 2020
[PDF]
U-net segmentation of tubular structures from live imaging confocal microscopy: Successes and challenges
K Arnavaz, P Nyeng, JM Krivokapic, O Krause, A Feragen
Early Career European Microscopy Congress 2020
[PDF]
Statistics on stratified spaces
A Feragen, T Nye
Riemannian Geometric Statistics in Medical Image Analysis, 2020
[Paper] [PDF] [bibtex]
TopAwaRe: Topology-Aware Registration
Rune Kok Nielsen, Sune Darkner, Aasa Feragen
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2019
[Paper] [bibtex] [code] [video]
A formalization of the natural gradient method for general similarity measures
A Mallasto, TD Haije, A Feragen
International Conference on Geometric Science of Information (GSI), 2019
[Paper] [bibtex]
Reconstructing objects from noisy images at low resolution
Helene Svane, Aasa Feragen
International Workshop on Graph-Based Representations in Pattern Recognition, 2019
[Paper] [bibtex]
Non-negative mean apparent propagators using sum-ofsquares optimization: MAP+
Tom Dela Haije, Evren Özarslan, Aasa Feragen
Proceedings of the 27th Annual Meeting of the ISMRM (International Society for Magnetic Resonance in Medicine), Montréal, 2019, p. 6900.
[Extended Abstract] [bibtex]
Quantifying spatial uncertainty in the space of curves: Streamline tractography
Emil Petersen, Victor Suadicani, Anton Mallasto, Tom Dela Haije, Aasa Feragen
International Symposium on Biomedical Imaging (ISBI), Venice, 2019, p. 852.
[PDF] [bibtex]
Statistics for Data with Geometric Structure
Aasa Feragen, Thomas Hotz, Stephan Huckemann, Ezra Miller
Oberwolfach Reports 15 (1), 125-186, 2019
[PDF] [bibtex]
(q, p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs
A Mallasto, J Frellsen, W Boomsma, A Feragen
arXiv preprint
[PDF] [bibtex]
Deterministic group tractography with local uncertainty quantification
Andreas Nugaard Holm, Aasa Feragen, Tom Dela Haije, Sune Darkner
Computational Diffusion MRI (CDMRI) Workshop at MICCAI 2018
[PDF] [bibtex]
Optimal Transport Distance between Wrapped Gaussian Distributions
Anton Mallasto, Aasa Feragen
MaxEnt 2018
[PDF] [bibtex]
Wrapped Gaussian Process Regression on Riemannian Manifolds
Anton Mallasto, Aasa Feragen
CVPR - IEEE Conference on Computer Vision and Pattern Recognition 2018
[PDF] [bibtex] [code]
Biases in classical structural parcellation
Michael Hejselbak Jensen, Henrik Thomsen, Matthew Liptrot, Niklas Kasenburg, Karl-Anton Dorph-Petersen, Sune Darkner, Aasa Feragen
Abstract, ISMRM - Annual Meeting for International Society for Magnetic Resonance in Medicine 2018
[Abstract] [bibtex]
The importance of constraints and spherical sampling in diffusion MRI
Tom Dela Haije, Aasa Feragen
Abstract, ISMRM - Annual Meeting for International Society for Magnetic Resonance in Medicine 2018
[Abstract] [bibtex]
Learning from graphs with structural variation
Rune Kok Nielsen, Andreas Nugaard Holm, A Feragen
NeurIPS 2017 workshop, Learning on Distributions, Functions, Graphs and Groups
[PDF] [bibtex] [code]
Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes
Anton Mallasto, Aasa Feragen
NeurIPS - Neural Information Processing Systems 2017: 5665-5674
[PDF] [bibtex] [code]