Dipy, a library for the analysis of diffusion MRI data E Garyfallidis, M Brett, B Amirbekian, A Rokem, S Van Der Walt, ... Frontiers in neuroinformatics 8, 8, 2014 | 1262 | 2014 |
QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data M Cieslak, PA Cook, X He, FC Yeh, T Dhollander, A Adebimpe, ... Nature methods 18 (7), 775-778, 2021 | 149* | 2021 |
Image Interpolation Techniques in Digital Image Processing S Fadnavis International Journal of Engineering Research and Applications 4 (10), 70-73, 2014 | 144 | 2014 |
Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning S Fadnavis, J Batson, E Garyfallidis Advances in Neural Information Processing Systems 33, 16293-16303, 2020 | 89 | 2020 |
Brainhack: Developing a culture of open, inclusive, community-driven neuroscience R Gau, S Noble, K Heuer, KL Bottenhorn, IP Bilgin, YF Yang, ... Neuron 109 (11), 1769-1775, 2021 | 34 | 2021 |
Pandora: 4-D white matter bundle population-based atlases derived from diffusion MRI fiber tractography CB Hansen, Q Yang, I Lyu, F Rheault, C Kerley, BQ Chandio, S Fadnavis, ... Neuroinformatics 19, 447-460, 2021 | 22 | 2021 |
Segmentation of the brain using direction-averaged signal of DWI images H Cheng, S Newman, M Afzali, SS Fadnavis, E Garyfallidis Magnetic resonance imaging 69, 1-7, 2020 | 18 | 2020 |
Denoising of diffusion MRI in the cervical spinal cord–effects of denoising strategy and acquisition on intra-cord contrast, signal modeling, and feature conspicuity KG Schilling*, S Fadnavis*, J Batson, M Visagie, AJE Combes, ... Neuroimage 266, 119826, 2023 | 16* | 2023 |
On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge. A De Luca, A Ianus, A Leemans, M Palombo, N Shemesh, H Zhang, ... NeuroImage 240, 2021 | 16 | 2021 |
Bifurcated topological optimization for IVIM S Fadnavis, S Endres, Q Wen, YC Wu, H Cheng, S Koudoro, S Rane, ... Frontiers in Neuroscience 15, 779025, 2021 | 10* | 2021 |
Nuq: A noise metric for diffusion mri via uncertainty discrepancy quantification S Fadnavis, J Sjölund, A Eklund, E Garyfallidis arXiv preprint arXiv:2203.01921, 2022 | 3 | 2022 |
Optimal partitioning methods for image segmentation S Fadnavis The Journal of Engineering 2015 (11), 341-344, 2015 | 2 | 2015 |
Accelerating medicines partnership® Schizophrenia (AMP® SCZ): Rationale and study design of the largest global prospective cohort study of clinical high risk for psychosis CMJ Wannan, B Nelson, J Addington, K Allott, A Anticevic, C Arango, ... Schizophrenia Bulletin 50 (3), 496-512, 2024 | 1 | 2024 |
Multi-scale V-net architecture with deep feature CRF layers for brain extraction JS Park, S Fadnavis, E Garyfallidis Communications Medicine 4 (1), 29, 2024 | 1* | 2024 |
Patch2Self denoising of diffusion MRI with self-supervision and matrix sketching S Fadnavis, A Chowdhury, J Batson, P Drineas, E Garyfallidis bioRxiv, 2022.03. 15.484539, 2022 | 1 | 2022 |
Bundleatlasing: unbiased population-specific atlasing of bundles in streamline space D Romero-Bascones, BQ Chandio, S Fadnavis, JS Park, S Koudoro, ... Proc. ISMRM, 2022 | 1 | 2022 |
MVD-Fuse: Detection of White Matter Degeneration via Multi-View Learning of Diffusion Microstructure S Fadnavis, P Polosecki, E Garyfallidis, E Castro, G Cecchi bioRxiv, 2021.04. 15.440095, 2021 | 1 | 2021 |
Denoising of DWI signal using deep learning H Cheng, J Wang, SS Fadnavis, E Garyfallidis, S Newman ISMRM 28th Annual Meeting, 2020 | 1 | 2020 |
Fusion of biomedical imaging studies for increased sample size and diversity: a case study of brain MRI M Aiskovich, E Castro, JM Reinen, S Fadnavis, A Mehta, H Li, ... Frontiers in Radiology 4, 1283392, 2024 | | 2024 |
Data-driven characterization of Preterm Birth through intramodal Diffusion MRI R Trò, M Roascio, D Tortora, M Severino, A Rossi, E Garyfallidis, ... bioRxiv, 2023.01. 12.523771, 2023 | | 2023 |