Jean Cousty

1.9k total citations
33 papers, 631 citations indexed

About

Jean Cousty is a scholar working on Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jean Cousty has authored 33 papers receiving a total of 631 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 6 papers in Computational Theory and Mathematics and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jean Cousty's work include Medical Image Segmentation Techniques (22 papers), Digital Image Processing Techniques (13 papers) and Visual Attention and Saliency Detection (7 papers). Jean Cousty is often cited by papers focused on Medical Image Segmentation Techniques (22 papers), Digital Image Processing Techniques (13 papers) and Visual Attention and Saliency Detection (7 papers). Jean Cousty collaborates with scholars based in France, Brazil and Algeria. Jean Cousty's co-authors include Laurent Najman, Michel Couprie, Gilles Bertrand, Silvio Jamil F. Guimarães, Benjamin Perret, Yukiko Kenmochi⋆, Stéphanie Clément-Guinaudeau, Jérôme Garot, Jean Serra and Hugues Talbot and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Jean Cousty

30 papers receiving 611 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jean Cousty France 12 445 97 71 68 54 33 631
S.N. Efstratiadis United States 13 830 1.9× 129 1.3× 228 3.2× 18 0.3× 94 1.7× 38 1.1k
F. Dibos France 4 1.1k 2.4× 156 1.6× 164 2.3× 28 0.4× 128 2.4× 8 1.3k
W.A. Sandham United Kingdom 12 295 0.7× 49 0.5× 71 1.0× 12 0.2× 148 2.7× 41 667
Luís Augusto Nagasaki Costa Brazil 6 273 0.6× 50 0.5× 19 0.3× 9 0.1× 38 0.7× 7 434
Nina S. T. Hirata Brazil 11 369 0.8× 25 0.3× 62 0.9× 34 0.5× 191 3.5× 67 586
Y.J. Zhang China 3 487 1.1× 64 0.7× 207 2.9× 12 0.2× 106 2.0× 5 744
Shilpa Suresh India 11 293 0.7× 29 0.3× 204 2.9× 24 0.4× 138 2.6× 47 558
Ikram E. Abdou United States 6 473 1.1× 62 0.6× 152 2.1× 10 0.1× 48 0.9× 13 643
T. Chang United States 5 797 1.8× 43 0.4× 325 4.6× 16 0.2× 124 2.3× 8 1.0k
Françoise Prêteux France 12 343 0.8× 74 0.8× 25 0.4× 11 0.2× 36 0.7× 67 505

Countries citing papers authored by Jean Cousty

Since Specialization
Citations

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

Fields of papers citing papers by Jean Cousty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jean Cousty

This figure shows the co-authorship network connecting the top 25 collaborators of Jean Cousty. A scholar is included among the top collaborators of Jean Cousty 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 Jean Cousty. Jean Cousty 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.
Saouli, Rachida, et al.. (2025). CD-GANs : Conditional dynamic training with GANs for enhanced post-gadolinium glioblastoma MRIs. Magnetic Resonance Imaging. 124. 110509–110509.
2.
Perret, Benjamin, et al.. (2025). Efficient Multiscale Object-based Superpixel Framework. Journal of the Brazilian Computer Society. 31(1). 355–372.
3.
Cousty, Jean, et al.. (2024). Incremental watershed cuts: Interactive segmentation algorithm with parallel strategy. Pattern Recognition Letters. 189. 256–263.
4.
Perret, Benjamin, et al.. (2023). Novel Arc-Cost Functions and Seed Relevance Estimations for Compact and Accurate Superpixels. Journal of Mathematical Imaging and Vision. 65(5). 770–786. 2 indexed citations
5.
Puybareau, Élodie, et al.. (2019). High throughput automated detection of axial malformations in Medaka embryo. Computers in Biology and Medicine. 105. 157–168. 4 indexed citations
6.
Perret, Benjamin, Jean Cousty, Silvio Jamil F. Guimarães, Yukiko Kenmochi⋆, & Laurent Najman. (2019). Removing non-significant regions in hierarchical clustering and segmentation. Pattern Recognition Letters. 128. 433–439. 8 indexed citations
7.
Perret, Benjamin, Giovanni Chierchia, Jean Cousty, et al.. (2019). Higra: Hierarchical Graph Analysis. SoftwareX. 10. 100335–100335. 19 indexed citations
8.
Cousty, Jean, Laurent Najman, Yukiko Kenmochi⋆, & Silvio Jamil F. Guimarães. (2017). Hierarchical Segmentations with Graphs: Quasi-flat Zones, Minimum Spanning Trees, and Saliency Maps. Journal of Mathematical Imaging and Vision. 60(4). 479–502. 30 indexed citations
9.
Cousty, Jean, et al.. (2017). Scale-space for empty catheter segmentation in PCI fluoroscopic images. International Journal of Computer Assisted Radiology and Surgery. 12(7). 1179–1188. 3 indexed citations
10.
Perret, Benjamin, et al.. (2017). Evaluation of Hierarchical Watersheds. IEEE Transactions on Image Processing. 27(4). 1676–1688. 26 indexed citations
11.
Lebenberg, Jessica, Alain Lalande, Patrick Clarysse, et al.. (2015). Improved Estimation of Cardiac Function Parameters Using a Combination of Independent Automated Segmentation Results in Cardiovascular Magnetic Resonance Imaging. PLoS ONE. 10(8). e0135715–e0135715. 6 indexed citations
12.
Lebenberg, Jessica, Irène Buvat, Alain Lalande, et al.. (2012). Nonsupervised Ranking of Different Segmentation Approaches: Application to the Estimation of the Left Ventricular Ejection Fraction From Cardiac Cine MRI Sequences. IEEE Transactions on Medical Imaging. 31(8). 1651–1660. 23 indexed citations
13.
14.
Cousty, Jean, et al.. (2010). Segmentation of 4D cardiac MRI: Automated method based on spatio-temporal watershed cuts. Image and Vision Computing. 28(8). 1229–1243. 60 indexed citations
15.
Cousty, Jean, Gilles Bertrand, Laurent Najman, & Michel Couprie. (2009). Watershed Cuts: Minimum Spanning Forests and the Drop of Water Principle. IEEE Transactions on Pattern Analysis and Machine Intelligence. 31(8). 1362–1374. 174 indexed citations
16.
Cousty, Jean, Gilles Bertrand, Laurent Najman, & Michel Couprie. (2009). Watershed Cuts: Thinnings, Shortest Path Forests, and Topological Watersheds. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32(5). 925–939. 102 indexed citations
17.
Cousty, Jean, Michel Couprie, Laurent Najman, & Gilles Bertrand. (2008). Weighted fusion graphs: Merging properties and watersheds. Discrete Applied Mathematics. 156(15). 3011–3027. 9 indexed citations
18.
Philipp‐Foliguet, Sylvie, et al.. (2008). Region-Based 3D Artwork Indexing and Classification. HAL (Le Centre pour la Communication Scientifique Directe). 393–396. 5 indexed citations
19.
Cousty, Jean, Gilles Bertrand, Michel Couprie, & Laurent Najman. (2007). Fusion Graphs: Merging Properties and Watersheds. Journal of Mathematical Imaging and Vision. 30(1). 87–104. 14 indexed citations
20.

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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