Carole Le Guyader

36 papers receiving 393 citations

Peers

Carole Le Guyader
Comparison fields: 5 of 69
  • Computer Vision and Pattern Recognition 311
  • Computational Mechanics 98
  • Radiology, Nuclear Medicine and Imaging 84
  • Biomedical Engineering 41
  • Artificial Intelligence 35
Replace Ganesh Sundaramoorthi with:
Ganesh Sundaramoorthi United States
Egil Bae Norway
Pavel Mrázek⋆ Germany
Feng Huang China
Luis Mazorra Spain
Marc Droske Germany
Triet Le United States
Andrés Solé Spain
Stéphanie Jehan‐Besson France
Adérito Araújo Portugal
Carole Le Guyader relative to Ganesh Sundaramoorthi United States Ganesh Sundaramoorthi's profile →
Citations per field
00.5×1.5×1.9×
Ganesh Sundaramoorthi · 1×
Citations per year

Countries citing papers authored by Carole Le Guyader

Since Specialization
Citations

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

Fields of papers citing papers by Carole Le Guyader

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Carole Le Guyader. 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 Carole Le Guyader. The network helps show where Carole Le Guyader may publish in the future.

Co-authorship network of co-authors of Carole Le Guyader

This figure shows the co-authorship network connecting the top 25 collaborators of Carole Le Guyader. A scholar is included among the top collaborators of Carole Le Guyader 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 Carole Le Guyader. Carole Le Guyader 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
#WorkIndexed citations
1 0
2 0
3 8
4 3
5 35
6 1
7 1
8 2
9 2
10 8
11 3
12 16
13 5
14 34
15 43
16 40
17 18
18 16
19 9
20
Kératose lichénoïde striée. forme congénitale.
4

About Carole Le Guyader

Carole Le Guyader is a scholar working on Computer Vision and Pattern Recognition, Modeling and Simulation and Radiology, Nuclear Medicine and Imaging, having authored 39 papers that have together received 426 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (25 papers), Medical Imaging Techniques and Applications (8 papers) and Advanced Numerical Analysis Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (311 citations), Computational Mechanics (98 citations) and Computer Graphics and Computer-Aided Design (16 citations). Carole Le Guyader has collaborated with scholars based in France, United States and Ireland. Frequent co-authors include Luminita A. Vese, Christian Gout, Nicolas Forcadel, Laurence Guillot, Paul M. Thompson, Arthur W. Toga, Lucia Romani, Ivo D. Dinov, Igor Yanovsky and Alex Leow. Their work appears in journals such as IEEE Transactions on Image Processing, Journal of Differential Equations and Computer Vision and Image Understanding.

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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