Laboratoire Traitement du Signal et de l'Image

64.6k citations
3.4k papers ·

Impact in

Papers in

Laboratoire Traitement du Signal et de l'Image

2.8k papers receiving 55.0k citations

Peers

Laboratoire Traitement du Signal et de l'Image
Comparison fields: 5 of 235
  • Cardiology and Cardiovascular Medicine 15.9k
  • Computational Mathematics 415
  • Cognitive Neuroscience 9.8k
  • Radiology, Nuclear Medicine and Imaging 9.4k
  • Signal Processing 3.9k
Replace Laboratoire d’Imagerie Biomédicale with:
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Laboratoire Traitement du Signal et de l'Image relative to Laboratoire d’Imagerie Biomédicale France Laboratoire d’Imagerie Biomédicale's profile →
Citations per field
00.5×5×10×12.7×
Laboratoire d’Imagerie Biomédicale · 1×
Citations per year

Countries citing scholars working at Laboratoire Traitement du Signal et de l'Image

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Laboratoire Traitement du Signal et de l'Image. 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 papers produced at Laboratoire Traitement du Signal et de l'Image with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laboratoire Traitement du Signal et de l'Image more than expected).

Fields of papers published by authors at Laboratoire Traitement du Signal et de l'Image

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Laboratoire Traitement du Signal et de l'Image at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Laboratoire Traitement du Signal et de l'Image at the time of their publication.

About Laboratoire Traitement du Signal et de l'Image

In recent decades, authors affiliated with Laboratoire Traitement du Signal et de l'Image have published 3.4k papers, which have received a total of 64.6k indexed citations . Scholars at this organization have produced 27 papers in Computational Mathematics, 705 papers in Cardiology and Cardiovascular Medicine, 560 papers in Radiology, Nuclear Medicine and Imaging, 289 papers in Signal Processing and 498 papers in Computer Vision and Pattern Recognition on the topics of EEG and Brain-Computer Interfaces (216 papers), Medical Image Segmentation Techniques (213 papers), Advanced MRI Techniques and Applications (182 papers), Blind Source Separation Techniques (171 papers), Cardiac Valve Diseases and Treatments (170 papers), Medical Imaging Techniques and Applications (168 papers), Neural dynamics and brain function (164 papers) and Cardiovascular Function and Risk Factors (150 papers). Their work is cited by papers focused on Cardiology and Cardiovascular Medicine (15.9k citations), Computational Mathematics (415 citations), Cognitive Neuroscience (9.8k citations), Radiology, Nuclear Medicine and Imaging (9.4k citations) and Signal Processing (3.9k citations). Authors at Laboratoire Traitement du Signal et de l'Image collaborate with scholars in France, United States and China and have published in prestigious journals including European Heart Journal - Cardiovascular Imaging, Archives of cardiovascular diseases, PLoS ONE, IEEE Transactions on Biomedical Engineering and International Journal of Computer Assisted Radiology and Surgery. Some of Laboratoire Traitement du Signal et de l'Image's most productive authors include Fabrice Wendling, Fabrice Bartoloméi, Patrick Chauvel, Patrick Flandrin, Jean-Louis Coatrieux, Jean-Jacques Bellanger, Erwan Donal, Lotfi Senhadji, Pierre Jannin and Huazhong Shu.

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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