Brian Cabral

2.9k citations
11 papers · 2.1k · 2 hit papers · h-index 8

Impact in

Papers in

Brian Cabral

11 papers receiving 1.9k citations

Brian Cabral's Hit Papers

Accelerated volume rendering and tomographic reconstruction using texture mapping hardware 1994 · 656 citations
6560+11+22Years since publication250500750

Peers

Brian Cabral
Comparison fields: 5 of 98
  • Computer Graphics and Computer-Aided Design 1.5k
  • Computer Vision and Pattern Recognition 1.3k
  • Computational Mechanics 978
  • Computational Mathematics 13
  • Geochemistry and Petrology 52
Replace Joe Kniss with:
Joe Kniss United States
Ronald Peikert Switzerland
B. C. McCallum New Zealand
Tino Weinkauf Germany
Ulrich Pinkall Germany
Jean‐Marie Morvan France
Thomas Lewiner Brazil
Ares Lagae Belgium
Xavier Tricoche United States
Michaël Gharbi United States
Brian Cabral relative to Joe Kniss United States Joe Kniss's profile →
Citations per field
00.5×1.5×
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Citations per year

Countries citing papers authored by Brian Cabral

Since Specialization
Citations

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

Fields of papers citing papers by Brian Cabral

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Brian Cabral, 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 Brian Cabral Line = papers co-authored together Brian Cabral links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1
Imaging vector fields using line integral convolution
Hit paper breakdown →
1993932
2
Accelerated volume rendering and tomographic reconstruction using texture mapping hardware
Hit paper breakdown →
1994656
3 1987154
4 199996
5 198784
6 199775
7 201940
8
Highly Parallel Vector Visualization Using Line Integral Convolution.
199510
9 20195
10 19945
11
NVIDIA Tegra
20083

About Brian Cabral

Brian Cabral is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Computational Mechanics, Geology and Radiology, Nuclear Medicine and Imaging, having authored 11 papers that have together received 2.1k indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (6 papers), Advanced Vision and Imaging (4 papers), Data Visualization and Analytics (3 papers), Medical Image Segmentation Techniques (2 papers), 3D Surveying and Cultural Heritage (2 papers), Multimodal Machine Learning Applications (1 paper), Interactive and Immersive Displays (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (1.5k citations), Computer Vision and Pattern Recognition (1.3k citations), Computational Mechanics (978 citations), Computational Mathematics (13 citations) and Geochemistry and Petrology (52 citations). Brian Cabral has collaborated with scholars based in United States, Israel and Pakistan. Frequent co-authors include Jim Foran, Nelson Max, Marc Olano, John Airey, Mark S. Peercy, Joyce Hsu, Alexander Sorkine‐Hornung, Rick Szeliski, S.G. Azevedo and J. Matheson. Their work appears in journals such as ACM Transactions on Graphics, ACM SIGGRAPH Computer Graphics, Pure (University of Bath), PPSC and Open MIND.

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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