Demián Wassermann

2.9k total citations
52 papers, 1.2k citations indexed

About

Demián Wassermann is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Demián Wassermann has authored 52 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Radiology, Nuclear Medicine and Imaging, 16 papers in Cognitive Neuroscience and 7 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Demián Wassermann's work include Advanced Neuroimaging Techniques and Applications (37 papers), Advanced MRI Techniques and Applications (20 papers) and Functional Brain Connectivity Studies (11 papers). Demián Wassermann is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (37 papers), Advanced MRI Techniques and Applications (20 papers) and Functional Brain Connectivity Studies (11 papers). Demián Wassermann collaborates with scholars based in France, United States and Argentina. Demián Wassermann's co-authors include Rachid Deriche, Rutger Fick, Maxime Descoteaux, Vinod Menon, Yogesh Rathi, Ragini Verma, Carl‐Fredrik Westin, Ron Kikinis, Martha E. Shenton and E.G. Kanterakis and has published in prestigious journals such as Nature Communications, NeuroImage and Cancer Research.

In The Last Decade

Demián Wassermann

49 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Demián Wassermann France 20 878 493 228 138 105 52 1.2k
Bagrat Amirbekian United States 9 1.1k 1.2× 476 1.0× 210 0.9× 123 0.9× 57 0.5× 12 1.4k
Huan Jiang China 4 1.4k 1.6× 700 1.4× 398 1.7× 193 1.4× 103 1.0× 5 1.7k
Pamela Guevara Chile 19 907 1.0× 636 1.3× 258 1.1× 96 0.7× 53 0.5× 68 1.3k
Jennifer S. W. Campbell Canada 14 930 1.1× 501 1.0× 212 0.9× 48 0.3× 37 0.4× 28 1.2k
Eleftherios Garyfallidis United States 19 1.7k 1.9× 724 1.5× 449 2.0× 159 1.2× 78 0.7× 44 2.2k
Hamied Haroon United Kingdom 17 1.1k 1.3× 551 1.1× 167 0.7× 67 0.5× 31 0.3× 32 1.5k
Fabrice Poupon France 18 620 0.7× 324 0.7× 119 0.5× 365 2.6× 139 1.3× 36 1.3k
Nicolás Lori Portugal 10 1.7k 1.9× 658 1.3× 541 2.4× 144 1.0× 55 0.5× 28 2.1k
Laura Rigolo United States 19 825 0.9× 487 1.0× 267 1.2× 68 0.5× 31 0.3× 36 1.1k
M. Okan İrfanoğlu United States 17 1.3k 1.5× 552 1.1× 268 1.2× 184 1.3× 61 0.6× 39 1.7k

Countries citing papers authored by Demián Wassermann

Since Specialization
Citations

This map shows the geographic impact of Demián Wassermann'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 Demián Wassermann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Demián Wassermann more than expected).

Fields of papers citing papers by Demián Wassermann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Demián Wassermann. 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 Demián Wassermann. The network helps show where Demián Wassermann may publish in the future.

Co-authorship network of co-authors of Demián Wassermann

This figure shows the co-authorship network connecting the top 25 collaborators of Demián Wassermann. A scholar is included among the top collaborators of Demián Wassermann 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 Demián Wassermann. Demián Wassermann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Scholz, Robert, Wei Wei, Carla Pallavicini, et al.. (2025). A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity. Scientific Reports. 15(1). 2849–2849. 2 indexed citations
2.
Scholz, Robert, Francesco Alberti, Rocco Chiou, et al.. (2024). A function-based mapping of sensory integration along the cortical hierarchy. Communications Biology. 7(1). 1593–1593. 2 indexed citations
3.
Pacella, Valentina, Victor Nozais, Lia Talozzi, et al.. (2024). The morphospace of the brain-cognition organisation. Nature Communications. 15(1). 8452–8452. 2 indexed citations
4.
Frangi, Alejandro F., Marleen de Bruijne, Demián Wassermann, & Nassir Navab. (2023). Information Processing in Medical Imaging. Lecture notes in computer science. 9 indexed citations
5.
Wassermann, Demián, et al.. (2023). A simulation-driven supervised learning framework to estimate brain microstructure using diffusion MRI. Medical Image Analysis. 90. 102979–102979. 1 indexed citations
6.
Leblanc, Judith, Demián Wassermann, Emmanuelle Kempf, et al.. (2021). Clinical Characteristics, Care Trajectories and Mortality Rate of SARS-CoV-2 Infected Cancer Patients: A Multicenter Cohort Study. Cancers. 13(19). 4749–4749. 10 indexed citations
7.
Chen, Lang, et al.. (2019). The visual word form area (VWFA) is part of both language and attention circuitry. Nature Communications. 10(1). 5601–5601. 102 indexed citations
8.
Fick, Rutger, Demián Wassermann, & Rachid Deriche. (2019). The Dmipy Toolbox: Diffusion MRI Multi-Compartment Modeling and Microstructure Recovery Made Easy. Frontiers in Neuroinformatics. 13. 64–64. 47 indexed citations
9.
Fick, Rutger, Alexandra Petiet, Mathieu Santin, et al.. (2018). Reducing the number of samples in spatiotemporal dMRI acquisition design. Magnetic Resonance in Medicine. 81(5). 3218–3233. 3 indexed citations
10.
Norton, Isaiah, Walid Ibn Essayed, Fan Zhang, et al.. (2017). SlicerDMRI: Open Source Diffusion MRI Software for Brain Cancer Research. Cancer Research. 77(21). e101–e103. 91 indexed citations
11.
Garyfallidis, Eleftherios, Omar Ocegueda, Demián Wassermann, & Maxime Descoteaux. (2015). Robust and efficient linear registration of white-matter fascicles in the space of streamlines. NeuroImage. 117. 124–140. 46 indexed citations
12.
Jolles, Dietsje, Demián Wassermann, Jennifer L. Richardson, et al.. (2015). Plasticity of left perisylvian white-matter tracts is associated with individual differences in math learning. Brain Structure and Function. 221(3). 1337–1351. 45 indexed citations
13.
Ross, James C., Alejandro A. Díaz, Yuka Okajima, et al.. (2014). Airway labeling using a Hidden Markov Tree Model. PubMed. 132. 554–558. 3 indexed citations
14.
Egger, Karl, Christian Clemm von Hohenberg, Michael Schocke, et al.. (2013). White Matter Changes in Patients with Friedreich Ataxia after Treatment with Erythropoietin. Journal of Neuroimaging. 24(5). 504–508. 17 indexed citations
15.
Wassermann, Demián, et al.. (2013). Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates. Frontiers in Neuroscience. 7. 260–260. 22 indexed citations
16.
Ghosh, Aurobrata, Demián Wassermann, & Rachid Deriche. (2011). A Polynomial Approach for Maxima Extraction and Its Application to Tractography in HARDI. Lecture notes in computer science. 22. 723–734. 5 indexed citations
17.
Wassermann, Demián, et al.. (2010). Diffusion-Based Population Statistics Using Tract Probability Maps. Lecture notes in computer science. 13(Pt 1). 631–639. 7 indexed citations
18.
Wassermann, Demián, Luke Bloy, E.G. Kanterakis, Ragini Verma, & Rachid Deriche. (2010). Unsupervised white matter fiber clustering and tract probability map generation: Applications of a Gaussian process framework for white matter fibers. NeuroImage. 51(1). 228–241. 99 indexed citations
19.
Delmaire, Christine, Marie Vidailhet, Demián Wassermann, et al.. (2009). Diffusion Abnormalities in the Primary Sensorimotor Pathways in Writer's Cramp. Archives of Neurology. 66(4). 502–8. 68 indexed citations
20.
Wassermann, Demián & Rachid Deriche. (2008). Simultaneous Manifold Learning and Clustering: Grouping White Matter Fiber Tracts Using a Volumetric White Matter Atlas. HAL (Le Centre pour la Communication Scientifique Directe). 9 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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