| Tractography and machine learning: Current state and open challenges P Poulin, D Jörgens, PM Jodoin, M Descoteaux Magnetic resonance imaging 64, 37-48, 2019 | 63 | 2019 |
| Challenges for tractogram filtering D Jörgens, M Descoteaux, R Moreno Anisotropy Across Fields and Scales, 149-168, 2021 | 14 | 2021 |
| Learning a single step of streamline tractography based on neural networks D Jörgens, Ö Smedby, R Moreno Computational Diffusion MRI: MICCAI Workshop, Québec, Canada, September 2017 …, 2018 | 11 | 2018 |
| Fiber orientation downsampling compromises the computation of white matter tract-related deformation Z Zhou, T Wang, D Jörgens, X Li journal of the mechanical behavior of biomedical materials 132, 105294, 2022 | 8 | 2022 |
| Towards a deep learning model for diffusion-aware tractogram filtering D Jörgens, P Poulin, R Moreno, PM Jodoin, M Descoteaux ISMRM 27th Annual Meeting & Exhibition, 11-16 May 2019, Montréal, QC, Canada, 2019 | 4 | 2019 |
| Tensor Voting: Current State, Challenges and New Trends in the Context of Medical Image Analysis. D Jörgens, R Moreno Visualization and Processing of Higher Order Descriptors for Multi-Valued …, 2015 | 3 | 2015 |
| Randomized iterative spherical‐deconvolution informed tractogram filtering A Hain, D Jörgens, R Moreno NeuroImage 278, 120248, 2023 | 2* | 2023 |
| Merging multiple input descriptors and supervisors in a deep neural network for tractogram filtering D Jörgens, PM Jodoin, M Descoteaux, R Moreno arXiv preprint arXiv:2307.05786, 2023 | 2 | 2023 |
| Voxel-wise clustering of tractography data for building atlases of local fiber geometry I Brusini, D Jörgens, Ö Smedby, R Moreno Computational Diffusion MRI: International MICCAI Workshop, Granada, Spain …, 2019 | 2 | 2019 |
| Segmentation of cortical bone using fast level sets M Chowdhury, D Jörgens, C Wang, Ö Smedby, R Moreno Medical Imaging 2017: Image Processing 10133, 610-616, 2017 | 2 | 2017 |
| Influence of tractography algorithms and settings on local curvature estimations I Brusini, D Jörgens, Ö Smedby, R Moreno Proceedings of OHBM Annual Meeting, 2017 | 2 | 2017 |
| Steering second-order tensor voting by vote clustering D Jörgens, Ö Smedby, R Moreno 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 1245-1248, 2016 | 1 | 2016 |
| Asymmetry in Cortical Thickness of the Heschl’s Gyrus in Unilateral Ear Canal Atresia M Siegbahn, D Jörgens, F Asp, M Hultcrantz, R Moreno, CE Berglin Otology & Neurotology, 10.1097, 2024 | | 2024 |
| Development and application of rule- and learning-based approaches within the scope of neuroimaging: Tensor voting, tractography and machine learning D Jörgens KTH Royal Institute of Technology, 2020 | | 2020 |
| Bias in Machine Learning und Konsequenzen für die Anwendung in der Marktforschung D Jörgens, Y Rieder, F Sinzinger Marktforschung für die Smart Data World, 137-156, 2020 | | 2020 |
| Dependency of neural tracts' curvature estimations on tractography methods I Brusini, D Jörgens, Ö Smedby, R Moreno Human Brain Project Student Conference, 2017 | | 2017 |
| Towards Grey Scale-Based Tensor Voting for Blood Vessel Analysis D Jörgens, R Moreno Modeling, Analysis, and Visualization of Anisotropy, 145-173, 2017 | | 2017 |
| Clustering of tensor votes for inference of fibre orientations in DTI data D Jörgens, Ö Smedby, R Moreno Proc. Swedish Society of Image Analysis (SSBA), 2016 | | 2016 |
Rodrigo MorenoAssociate Professor, KTH Royal Institute of TechnologyVerified email at sth.kth.se
