Luc Florack

4.0k total citations
101 papers, 1.8k citations indexed

About

Luc Florack is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Cognitive Neuroscience. According to data from OpenAlex, Luc Florack has authored 101 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Computer Vision and Pattern Recognition, 39 papers in Radiology, Nuclear Medicine and Imaging and 11 papers in Cognitive Neuroscience. Recurrent topics in Luc Florack's work include Medical Image Segmentation Techniques (34 papers), Advanced Neuroimaging Techniques and Applications (29 papers) and Image Retrieval and Classification Techniques (21 papers). Luc Florack is often cited by papers focused on Medical Image Segmentation Techniques (34 papers), Advanced Neuroimaging Techniques and Applications (29 papers) and Image Retrieval and Classification Techniques (21 papers). Luc Florack collaborates with scholars based in Netherlands, Germany and Denmark. Luc Florack's co-authors include Bart M. ter Haar Romeny, Max A. Viergever, Jan J. Koenderink, Arjan Kuijper, Mads Nielsen, Hans C. van Assen, Remco Duits, Jon Sporring, Peter Johansen and Rachid Deriche and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, NeuroImage and IEEE Transactions on Image Processing.

In The Last Decade

Luc Florack

92 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luc Florack Netherlands 19 1.1k 379 212 149 133 101 1.8k
Fabrice Heitz France 22 1.1k 1.0× 348 0.9× 250 1.2× 70 0.5× 269 2.0× 100 1.7k
Mikaël Rousson United States 16 1.4k 1.2× 424 1.1× 183 0.9× 114 0.8× 224 1.7× 23 1.8k
D.M. Healy United States 16 1.1k 0.9× 218 0.6× 379 1.8× 33 0.2× 113 0.8× 32 2.0k
Andrés Bruhn Germany 19 2.5k 2.2× 209 0.6× 449 2.1× 62 0.4× 157 1.2× 52 3.0k
David H. Marimont United States 9 1.6k 1.4× 133 0.4× 517 2.4× 64 0.4× 55 0.4× 15 2.0k
Dmitry Ulyanov Russia 6 1.6k 1.4× 294 0.8× 441 2.1× 50 0.3× 356 2.7× 6 2.5k
William M. Wells United States 15 2.2k 1.9× 754 2.0× 269 1.3× 92 0.6× 300 2.3× 40 3.1k
Suyash P. Awate United States 22 715 0.6× 545 1.4× 263 1.2× 55 0.4× 188 1.4× 85 1.5k
Y.Y. Zeevi Israel 20 2.0k 1.7× 144 0.4× 641 3.0× 68 0.5× 144 1.1× 108 2.7k
Alain Horé Canada 8 2.0k 1.7× 297 0.8× 746 3.5× 64 0.4× 269 2.0× 16 2.8k

Countries citing papers authored by Luc Florack

Since Specialization
Citations

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

Fields of papers citing papers by Luc Florack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luc Florack

This figure shows the co-authorship network connecting the top 25 collaborators of Luc Florack. A scholar is included among the top collaborators of Luc Florack 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 Luc Florack. Luc Florack 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.
Baene, Wouter De, et al.. (2025). Presurgical structural connectivity predicts postsurgical cognitive impairment in glioma patients. Brain Communications. 7(5). fcaf346–fcaf346.
2.
Baene, Wouter De, et al.. (2024). Can structure predict function at individual level in the human connectome?. Brain Structure and Function. 229(5). 1209–1223. 2 indexed citations
3.
Rutten, Geert‐Jan, et al.. (2023). Subject-Specific Automatic Reconstruction of White Matter Tracts. Journal of Digital Imaging. 36(6). 2648–2661. 7 indexed citations
4.
Baene, Wouter De, et al.. (2023). Working memory performance in glioma patients is associated with functional connectivity between the right dorsolateral prefrontal cortex and default mode network. Journal of Neuroscience Research. 101(12). 1826–1839. 8 indexed citations
5.
Ossenblok, Pauly, Albert Colon, Louis Wagner, et al.. (2018). Modeling of intracerebral interictal epileptic discharges: Evidence for network interactions. Clinical Neurophysiology. 129(6). 1276–1290. 5 indexed citations
6.
Tax, Chantal M. W., A. Fuster, Carl‐Fredrik Westin, et al.. (2016). Sheet Probability Index (SPI): Characterizing the geometrical organization of the white matter with diffusion MRI. NeuroImage. 142. 260–279. 12 indexed citations
7.
Graaf, Wolter L. de, et al.. (2014). Functional imaging of murine hearts using accelerated self-gated UTE cine MRI. International journal of cardiac imaging. 31(1). 83–94. 10 indexed citations
8.
Florack, Luc, et al.. (2013). Riemann-Finsler geometry and its applications to diffusion magnetic resonance imaging. Data Archiving and Networked Services (DANS). 1(8). 61–6. 1 indexed citations
9.
Duits, Remco, et al.. (2010). Cardiac motion estimation using covariant derivatives and Helmholtz decomposition. TU/e Research Portal (Eindhoven University of Technology). 1031. 1 indexed citations
10.
Florack, Luc & Hans C. van Assen. (2010). A New Methodology for Multiscale Myocardial Deformation and Strain Analysis Based on Tagging MRI. International Journal of Biomedical Imaging. 2010(1). 341242–341242. 9 indexed citations
11.
Florack, Luc, et al.. (2008). A multi-resolution framework for diffusion tensor images. TU/e Research Portal (Eindhoven University of Technology). 810. 5 indexed citations
12.
Olsen, Ole Fogh, Luc Florack, & Arjan Kuijper. (2006). Deep Structure, Singularities, and Computer Vision: First International Workshop, DSSCV 2005, Maastricht, The Netherlands, June 9-10, 2005, Revised Selected Papers (Lecture Notes in Computer Science). Springer eBooks. 5 indexed citations
13.
Suinesiaputra, Avan, Luc Florack, Jos J.M. Westenberg, et al.. (2003). Optic Flow Computation from Cardiac MR Tagging Using a Multiscale Differential Method A Comparative Study with Velocity-Encoded MRI. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 483–490. 4 indexed citations
14.
Kuijper, Arjan & Luc Florack. (2003). The hierarchical structure of images. IEEE Transactions on Image Processing. 12(9). 1067–1079. 11 indexed citations
15.
Vassiliadis, S., et al.. (2003). A design system based on generic representations. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 302(3). 275–83. 3 indexed citations
16.
Kuijper, Arjan & Luc Florack. (2002). Logical Filtering in Scale Space. Utrecht University Repository (Utrecht University). 8 indexed citations
17.
Kuijper, Arjan, et al.. (2001). Scale Space Hierarchy. TU/e Research Portal (Eindhoven University of Technology). 3 indexed citations
18.
Florack, Luc. (1998). Non-linear scale-spaces isomorphic to the linear case. Data Archiving and Networked Services (DANS). 1 indexed citations
19.
Florack, Luc, et al.. (1997). The intrinsic structure of optic flow incorporating measurement duality. TU/e Research Portal (Eindhoven University of Technology). 1 indexed citations
20.
Nielsen, Mads, Luc Florack, & Rachid Deriche. (1994). Regularization and Scale Space. OpenGrey (Institut de l'Information Scientifique et Technique). 21 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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