Benjamin De Leener

2.7k total citations · 1 hit paper
33 papers, 1.3k citations indexed

About

Benjamin De Leener is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Pathology and Forensic Medicine. According to data from OpenAlex, Benjamin De Leener has authored 33 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Surgery and 9 papers in Pathology and Forensic Medicine. Recurrent topics in Benjamin De Leener's work include Advanced Neuroimaging Techniques and Applications (17 papers), Advanced MRI Techniques and Applications (8 papers) and Medical Imaging and Analysis (8 papers). Benjamin De Leener is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (17 papers), Advanced MRI Techniques and Applications (8 papers) and Medical Imaging and Analysis (8 papers). Benjamin De Leener collaborates with scholars based in Canada, United States and France. Benjamin De Leener's co-authors include Julien Cohen‐Adad, Virginie Callot, Vladimir Fonov, D. Louis Collins, Nikola Stikov, Samuel Kadoury, Sara M. Dupont, Simon Lévy, Manuel Taso and Michael G. Fehlings and has published in prestigious journals such as PLoS ONE, NeuroImage and Brain.

In The Last Decade

Benjamin De Leener

29 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data

2016 376 citations Benjamin De Leener, Simon Lévy et al. NeuroImage profile →

Peers

Benjamin De Leener

RNMI

PFM

SURGE

PHEOH

Henrik Lundell Denmark

Sara M. Dupont United States

Jeffrey P. Mullin United States

Eftychia Z. Kapsalaki Greece

Kouhei Kamiya Japan

Mark C. DeLano United States

Xing‐Chang Wei Canada

Kenji Ino Japan

Ulrich‐Wilhelm Thomale Germany

Maria Marcella Laganà Italy

Henrik Lundell Denmark

Benjamin De Leener

835 ×1.3

RNMI

367 ×0.7

PFM

113 ×0.3

SURGE

161 ×0.6

57 ×0.3

PHEOH

Citations per year, relative to Benjamin De Leener Benjamin De Leener (= 1×) peers Henrik Lundell

Countries citing papers authored by Benjamin De Leener

Since Specialization

Citations

This map shows the geographic impact of Benjamin De Leener's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Benjamin De Leener with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin De Leener more than expected).

Fields of papers citing papers by Benjamin De Leener

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin De Leener. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Benjamin De Leener. The network helps show where Benjamin De Leener may publish in the future.

Co-authorship network of co-authors of Benjamin De Leener

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin De Leener. A scholar is included among the top collaborators of Benjamin De Leener based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Benjamin De Leener. Benjamin De Leener is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Dahlberg, Linda Solstrand, et al.. (2025). Parkinson’s disease in the spinal cord: An exploratory study to establish T2*w, MTR and diffusion-weighted imaging metric values. Imaging Neuroscience. 3.

Kinany, Nawal, Benjamin De Leener, Ovidiu Lungu, et al.. (2024). Cerebro-spinal somatotopic organization uncovered through functional connectivity mapping. Imaging Neuroscience. 2.

Weber, Kenneth A., Christine Law, Sean Mackey, et al.. (2024). Three-dimensional spatial distribution of lumbar paraspinal intramuscular fat revealed by spatial parametric mapping. European Spine Journal. 34(1). 27–35. 1 indexed citations

Pool‐Goudzwaard, Annelies, Benjamin De Leener, Christine Law, et al.. (2024). Investigating the associations between lumbar paraspinal muscle health and age, BMI, sex, physical activity, and back pain using an automated computer-vision model: a UK Biobank study. The Spine Journal. 24(7). 1253–1266. 19 indexed citations

Kinany, Nawal, et al.. (2023). In vivo parcellation of the human spinal cord functional architecture. Imaging Neuroscience. 2. 4 indexed citations

Dahlberg, Linda Solstrand, et al.. (2023). Altered Spinal Cord Functional Connectivity Associated with Parkinson's Disease Progression. Movement Disorders. 38(4). 636–645. 14 indexed citations

Londoño, Irene, Benjamin De Leener, Sophie Wang, et al.. (2023). Severe central nervous system demyelination in Sanfilippo disease. Frontiers in Molecular Neuroscience. 16. 1323449–1323449. 5 indexed citations

Leener, Benjamin De, Mahdi Alizadeh, Adam E. Flanders, et al.. (2021). Atlas-Based Quantification of DTI Measures in a Typically Developing Pediatric Spinal Cord. American Journal of Neuroradiology. 42(9). 1727–1734. 5 indexed citations

Mangeat, Gabriel, Russell Ouellette, Benjamin De Leener, et al.. (2020). Machine Learning and Multiparametric Brain MRI to Differentiate Hereditary Diffuse Leukodystrophy with Spheroids from Multiple Sclerosis. Journal of Neuroimaging. 30(5). 674–682. 19 indexed citations

10.

Ouellette, Russell, Constantina A. Treaba, Tobias Granberg, et al.. (2020). 7 T imaging reveals a gradient in spinal cord lesion distribution in multiple sclerosis. Brain. 143(10). 2973–2987. 25 indexed citations

11.

Martin, Allan R., Benjamin De Leener, Julien Cohen‐Adad, et al.. (2018). Can microstructural MRI detect subclinical tissue injury in subjects with asymptomatic cervical spinal cord compression? A prospective cohort study. BMJ Open. 8(4). e019809–e019809. 58 indexed citations

12.

Martin, Allan R., Benjamin De Leener, Julien Cohen‐Adad, et al.. (2018). Monitoring for myelopathic progression with multiparametric quantitative MRI. PLoS ONE. 13(4). e0195733–e0195733. 53 indexed citations

13.

Martin, Allan R., Benjamin De Leener, Julien Cohen‐Adad, et al.. (2017). Clinically Feasible Microstructural MRI to Quantify Cervical Spinal Cord Tissue Injury Using DTI, MT, and T2*-Weighted Imaging: Assessment of Normative Data and Reliability. American Journal of Neuroradiology. 38(6). 1257–1265. 52 indexed citations

14.

Dupont, Sara M., Benjamin De Leener, Manuel Taso, et al.. (2016). Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter. NeuroImage. 150. 358–372. 35 indexed citations

15.

Leener, Benjamin De, Simon Lévy, Sara M. Dupont, et al.. (2016). SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. NeuroImage. 145(Pt A). 24–43. 376 indexed citations breakdown →

16.

Martin, Allan R., Benjamin De Leener, Julien Cohen‐Adad, et al.. (2016). 163 Microstructural MRI Quantifies Tract-Specific Injury and Correlates With Global Disability and Focal Neurological Deficits in Degenerative Cervical Myelopathy. Neurosurgery. 63(Supplement 1). 165–165. 8 indexed citations

17.

Leener, Benjamin De, Manuel Taso, Julien Cohen‐Adad, & Virginie Callot. (2016). Segmentation of the human spinal cord. Magnetic Resonance Materials in Physics Biology and Medicine. 29(2). 125–153. 50 indexed citations

18.

Yiannakas, Marios, Ahmed M. Mustafa, Benjamin De Leener, et al.. (2015). Fully automated segmentation of the cervical cord from T1-weighted MRI using PropSeg: Application to multiple sclerosis. NeuroImage Clinical. 10. 71–77. 51 indexed citations

19.

Leener, Benjamin De, Samuel Kadoury, & Julien Cohen‐Adad. (2014). Robust, accurate and fast automatic segmentation of the spinal cord. NeuroImage. 98. 528–536. 120 indexed citations

20.

Fonov, Vladimir, Arnaud Le Troter, Manuel Taso, et al.. (2014). Framework for integrated MRI average of the spinal cord white and gray matter: The MNI–Poly–AMU template. NeuroImage. 102. 817–827. 81 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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