🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Koen Van Leemput

Aalto University

ORCID: 0000-0001-6466-5309
Computer ScienceMedicineNeuroscience

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 4%percentile
0.630Author DataRank

Indexed papers

2in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 2 indexed papers attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

The Journal of Machine Learning for Biomedical Imaging(2025)10.59275/j.melba.2025-9bd3
Top 49%
0.361DataRank
Top 49%7 citations

Anastasia Janas, Ujjwal Baid, Divya Ramakrishnan, Rachit Saluja, Nader A. Fawzy +95 more

Papers

Driven by 22 papers — median percentile 46. Top paper: “An open-source tool for longitudinal whole-brain and white matter lesion segmentation”.

An open-source tool for longitudinal whole-brain and white matter lesion segmentation

NeuroImage Clinical(2023)10.1016/j.nicl.2023.103354
N/A
0.529DataRank · unranked
33 citations

Douglas N. Greve, Andrew Hoopes, Henrik Lundell, Hartwig R. Siebner, Mark Mühlau +2 more

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma

arXiv (Cornell University)(2023)10.48550/arxiv.2305.07642
N/A
0.494DataRank · unranked
26 citations

Maruf Adewole, Michelle Alonso‐Basanta, Talissa A. Altes, Syed Muhammad Anwar, Ujjwal Baid +55 more

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

The Journal of Machine Learning for Biomedical Imaging(2025)10.59275/j.melba.2025-9bd3
Top 49%
0.361DataRank
Top 49%7 citations

Anastasia Janas, Ujjwal Baid, Divya Ramakrishnan, Rachit Saluja, Nader A. Fawzy +95 more

Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology

eLife(2023)10.7554/elife.91398
N/A
0.330DataRank · unranked
8 citations

Henry F. J. Tregidgo, Benjamin Billot, Yaël Balbastre, Jonathan Williams-Ramirez, Rogeny Herisse +21 more

Assessing individual variability of the entorhinal subfields in health and disease

The Journal of Comparative Neurology(2023)10.1002/cne.25538
Top 58%
0.269DataRank
Top 58%4 citations

Douglas N. Greve, Stefano Cerri, Natalya Slepneva, Josué Llamas Rodríguez, Juan Eugenio Iglesias +5 more

A Contrast‐Agnostic Method for Ultra‐High Resolution Claustrum Segmentation

Human Brain Mapping(2025)10.1002/hbm.70303
N/A
0.241DataRank · unranked
4 citations

Ryan Fritz, Jocelyn Mora, Benjamin Billot, Juan Eugenio Iglesias, Koen Van Leemput +3 more

Accurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas

NeuroImage(2023)10.1016/j.neuroimage.2023.120129
N/A
0DataRank · unranked
28 citations

Sonja Soskic, Juri Althonayan, Chiara Maffei, Koen Van Leemput, Polina Golland +10 more

Accurate and robust whole-head segmentation from magnetic resonance images for individualized head modeling

NeuroImage(2020)10.1016/j.neuroimage.2020.117044
N/A
0DataRank · unranked
245 citations

Koen Van Leemput, Guilherme B. Saturnino, Hartwig R. Siebner, Kristoffer H. Madsen, Axel Thielscher +1 more

Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.06.08.544050
N/A
0DataRank · unranked
4 citations

Henry F. J. Tregidgo, Benjamin Billot, Yaël Balbastre, Jonathan Williams-Ramirez, Rogeny Herisse +21 more

Intensity scaling of conventional brain magnetic resonance images avoiding cerebral reference regions: A systematic review

PLoS ONE(2024)10.1371/journal.pone.0298642
N/A
0DataRank · unranked
6 citations

Cui Ci Voon, Koen Van Leemput, Benedikt Wiestler, Mark Mühlau, Tun Wiltgen

Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology

eLife(2024)10.7554/elife.91398.4
N/A
0DataRank · unranked
1 citations

Henry F. J. Tregidgo, Benjamin Billot, Yaël Balbastre, Jonathan Williams-Ramirez, Rogeny Herisse +21 more

The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

arXiv (Cornell University)(2024)10.48550/arxiv.2404.15009
N/A
0DataRank · unranked
7 citations

Nastaran Khalili, Xinyang Liu, Deep Gandhi, Zhifan Jiang, Syed Muhammed Anwar +66 more

Reviewer #1 (Public Review): Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology

(2024)10.7554/elife.91398.2.sa1
N/A
0DataRank · unranked
0 citations

Henry F. J. Tregidgo, Benjamin Billot, Yael Balbastre, Jonathan William-Ramirez, Rogeny Herisse +21 more

Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology

eLife(2024)10.7554/elife.91398.2
N/A
0DataRank · unranked
0 citations

Henry F. J. Tregidgo, Benjamin Billot, Yaël Balbastre, Jonathan William-Ramirez, Rogeny Herisse +21 more

Reviewer #2 (Public Review): Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology

(2024)10.7554/elife.91398.3.sa0
N/A
0DataRank · unranked
0 citations

Henry F. J. Tregidgo, Benjamin Billot, Yael Balbastre, Jonathan William-Ramirez, Rogeny Herisse +21 more

Hierarchical Uncertainty Estimation for Learning-based Registration in Neuroimaging

arXiv (Cornell University)(2024)10.48550/arxiv.2410.09299
N/A
0DataRank · unranked
0 citations

Karthik Gopinath, Peirong Liu, Malte Hoffmann, Koen Van Leemput, Oula Puonti +2 more

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)

arXiv (Cornell University)(2023)10.48550/arxiv.2305.09011
N/A
0DataRank · unranked
12 citations

Gian Marco Conte, Hu, Qingqiao, Syed Muhammad Anwar, Florian Kofler, Ivan Ezhov +60 more

Reliability and sensitivity of two whole-brain segmentation approaches included in FreeSurfer – ASEG and SAMSEG

NeuroImage(2021)10.1016/j.neuroimage.2021.118113
N/A
0DataRank · unranked
32 citations

Didac Vidal‐Piñeiro, Øystein Sørensen, Koen Van Leemput, Juan Eugenio Iglesias, Adrian V. Dalca +6 more

A Contrast Augmentation Approach to Improve Multi-Scanner Generalization in MRI

Frontiers in Neuroscience(2021)10.3389/fnins.2021.708196
N/A
0DataRank · unranked
25 citations

Ezequiel de la Rosa, Nuno Pedrosa de Barros, Roberto Paolella, Koen Van Leemput, Diana M. Sima +1 more

An Augmentation Strategy to Mimic Multi-Scanner Variability in MRI

arXiv (Cornell University)(2021)10.1109/isbi48211.2021.9433833
N/A
0DataRank · unranked
0 citations

Ezequiel de la Rosa, Nuno Pedrosa de Barros, Roberto Paolella, Koen Van Leemput, Diana M. Sima +1 more

A robust intensity distribution alignment for harmonization of T1w intensity values

bioRxiv (Cold Spring Harbor Laboratory)(2022)10.1101/2022.06.15.496227
N/A
0DataRank · unranked
4 citations

Atle Bjørnerud, Kristine B. Walhovd, Koen Van Leemput, Bruce Fischl, Anders M. Fjell +1 more

SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining

Medical Image Analysis(2023)10.1016/j.media.2023.102789
N/A
0DataRank · unranked
579 citations

Douglas N. Greve, Oula Puonti, Axel Thielscher, Koen Van Leemput, Bruce Fischl +3 more