Brian B. Avants

Computer Vision and Pattern Recognition · 2004–2021

A researcher in the Science corpus: 14 papers; trusts 28 researchers and is trusted by 59 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 138 citations into it; #3,863 of 21,575 by trust here, #1,237 by citations
• Radiology, Nuclear Medicine and Imaging — 71 citations into it; #389 of 3,265 by trust here, #185 by citations
• Artificial Intelligence — 28 citations into it
• Geometry and Topology — 19 citations into it
• Biomedical Engineering — 17 citations into it; #1,420 of 10,734 by trust here, #4,640 by citations
• Biophysics — 17 citations into it; #257 of 1,196 by trust here, #218 by citations
• Computational Mechanics — 11 citations into it; #2,165 of 10,001 by trust here, #1,325 by citations
• Media Technology — 9 citations into it

Whom Brian B. Avants trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Eric Learned-Miller
2. John Ashburner
3. Michael I. Miller
4. Daniel Rueckert
5. Julian Besag
6. Terry S. Yoo
7. Gary E. Christensen
8. John P. Lewis
9. Hans J. Johnson
10. Sarang C. Joshi

Who trusts Brian B. Avants overall

1. Guha Balakrishnan
2. Nicholas J. Tustison
3. Tony C. W. Mok
4. P. Cook
5. Paul Yushkevich
6. Adrian V. Dalca
7. Heung-Il Suk
8. Martin Reuter
9. Amy Zhao
10. Shengyu Zhao

Papers from Brian B. Avants's perspective

Ordered by how strongly the researchers Brian B. Avants trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation (IEEE Transactions on Medical Imaging)
3. Automatic anatomical brain MRI segmentation combining label propagation and decision fusion (NeuroImage)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. On Combining Classifiers
6. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
7. Consistent image registration (IEEE Transactions on Medical Imaging)
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. HAMMER: hierarchical attribute matching mechanism for elastic registration (IEEE Transactions on Medical Imaging)
10. Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms (International Journal of Computer Vision)

Their papers

• The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) (2015) — 6,325 citations
• N4ITK: Improved N3 Bias Correction (2010) — 5,727 citations
• A Reproducible Evaluation of ANTs Similarity Metric Performance in Brain Image Registration (2010) — 4,637 citations
• Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge (2011) — 492 citations
• Geodesic estimation for large deformation anatomical shape averaging and interpolation. (2004) — 460 citations
• Advanced Normalization Tools (ANTs) (2020) — 1,589 citations
• The ANTsX ecosystem for quantitative biological and medical imaging (2021) — 419 citations
• The Insight ToolKit image registration framework (2014) — 644 citations
• Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements (2014) — 676 citations
• An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data (2011) — 583 citations
• Evaluation of volume-based and surface-based brain image registration methods (2010)
• The Optimal Template Effect in Hippocampus Studies of Diseased Populations (2009) — 644 citations
• Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration (2009) — 2,380 citations
• Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain (2008) — 5,742 citations