Pascal Cachier

972 citations
8 papers · 381 indexed · h-index 7

Impact in

Papers in

Pascal Cachier

8 papers receiving 357 citations

Peers

Pascal Cachier
Comparison fields: 5 of 51
  • Computer Vision and Pattern Recognition 264
  • Radiology, Nuclear Medicine and Imaging 206
  • Radiation 47
  • Computational Mathematics 2
  • Biophysics 16
Replace Manav Bhushan with:
Manav Bhushan United Kingdom
Rainer Sprengel Germany
K. Rohr Germany
Steven L. Hartmann United States
Valérie Duay Switzerland
Martin Groher Germany
Bartłomiej W. Papież United Kingdom
Márta Fidrich Hungary
Outi Sipilä Finland
Daniel B. Russakoff United States
Pascal Cachier relative to Manav Bhushan United Kingdom Manav Bhushan's profile →
Citations per field
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Manav Bhushan · 1×
Citations per year

Countries citing papers authored by Pascal Cachier

Since Specialization
Citations

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

Fields of papers citing papers by Pascal Cachier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 5 scholars most cited alongside Pascal Cachier, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pascal Cachier Line = papers co-authored together Pascal Cachier links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 2003176
2
Fast Non Rigid Matching by Gradient Descent: Study and Improvements of the "Demons" Algorithm
199958
3 200244
4 200440
5 200236
6 200215
7
Regularization in Image Non-Rigid Registration: I. Trade-off between Smoothness and Intensity Similarity
20018
8
Regularization Methods in Non-Rigid Registration :II. Isotropic Energies, Filters and Splines
20014

About Pascal Cachier

Pascal Cachier is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition, Computational Mechanics, Radiology, Nuclear Medicine and Imaging and Aerospace Engineering, having authored 8 papers that have together received 381 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (7 papers), Robotics and Sensor-Based Localization (4 papers), 3D Shape Modeling and Analysis (3 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Medical Imaging Techniques and Applications (2 papers), Advanced Vision and Imaging (2 papers), Optical measurement and interference techniques (1 paper) and Tensor decomposition and applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (264 citations), Radiology, Nuclear Medicine and Imaging (206 citations), Radiation (47 citations), Computational Mathematics (2 citations) and Biophysics (16 citations). Pascal Cachier has collaborated with scholars based in France. Frequent co-authors include Nicholas Ayache, Xavier Pennec, Éric Bardinet, Didier Dormont and Alexis Roche. Their work appears in journals such as Pattern Recognition Letters, Computer Vision and Image Understanding, Journal of Mathematical Imaging and Vision, OpenGrey (Institut de l'Information Scientifique et Technique) and HAL (Le Centre pour la Communication Scientifique Directe).

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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