D. Larose

713 citations
14 papers · 595 · h-index 9

Impact in

Papers in

D. Larose

14 papers receiving 567 citations

Peers

D. Larose
Comparison fields: 5 of 60
  • Computer Vision and Pattern Recognition 206
  • Biomedical Engineering 406
  • Computer Graphics and Computer-Aided Design 26
  • Surgery 230
  • Control and Systems Engineering 125
Replace Jörg Raczkowsky with:
Jörg Raczkowsky Germany
B.L. Musits United States
Martin Gröger Germany
Douglas P. Perrin United States
Hadrien Courtecuisse France
Omid Mohareri Canada
Philippe Zanne France
J. Zuhars United States
D. Glauser Switzerland
Cinzia Freschi Italy
D. Larose relative to Jörg Raczkowsky Germany Jörg Raczkowsky's profile →
Citations per field
00.5×5.2×
Jörg Raczkowsky · 1×
Citations per year

Countries citing papers authored by D. Larose

Since Specialization
Citations

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

Fields of papers citing papers by D. Larose

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside D. Larose, 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 D. Larose Line = papers co-authored together D. Larose links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 1995345
2
Iterative x-ray/ct registration using accelerated volume rendering
200156
3
Augmentation of human precision in computer-integrated surgery
199240
4 199635
5 199231
6 200030
7 199320
8 200019
9 20068
10
A Fast, Affordable System for Augmented Reality
19984
11 20033
12 20022
13 20101
14 20021

About D. Larose

D. Larose is a scholar working on Surgery, Computer Vision and Pattern Recognition, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Aerospace Engineering, having authored 14 papers that have together received 595 indexed citations. Recurring topics across this work include Surgical Simulation and Training (5 papers), Augmented Reality Applications (4 papers), Soft Robotics and Applications (3 papers), Medical Imaging Techniques and Applications (3 papers), Medical Image Segmentation Techniques (2 papers), Medical Imaging and Analysis (2 papers), Computer Graphics and Visualization Techniques (2 papers) and Robotics and Sensor-Based Localization (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (206 citations), Biomedical Engineering (406 citations), Computer Graphics and Computer-Aided Design (26 citations), Surgery (230 citations) and Control and Systems Engineering (125 citations). D. Larose has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include J. Funda, Russell H. Taylor, Kreg G. Gruben, James H. Anderson, Benjamin N. Eldridge, Takeo Kanade, Mark A. Talamini, Louis R. Kavoussi, John E. Bayouth and Michael R. Treat. Their work appears in journals such as Lecture notes in control and information sciences, Robotica, Lecture notes in computer science, IEEE Engineering in Medicine and Biology Magazine and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

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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