K. V. Leemput

Computer Vision and Pattern Recognition · 2001–2018

A researcher in the Science corpus: 9 papers; trusts 11 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 69 citations into it; #10,081 of 21,575 by trust here, #2,587 by citations
• Radiology, Nuclear Medicine and Imaging — 49 citations into it; #2,205 of 3,265 by trust here, #2,127 by citations
• Cognitive Neuroscience — 29 citations into it
• Molecular Biology — 13 citations into it
• Statistics and Probability — 10 citations into it; #10,662 of 12,932 by trust here, #8,279 by citations
• Physiology — 8 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it
• Statistical Learning Theory — 5 citations into it

Whom K. V. Leemput trusts overall

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

1. Arthur P. Dempster
2. Greg C. G. Wei
3. Nan M. Laird
4. David W. Shattuck
5. Donald B. Rubin
6. Martin A. Tanner
7. Rolf A. Heckemann
8. Réka Albert
9. Bruce Fischl
10. R. Fisher

Who trusts K. V. Leemput overall

1. Alex P. Zijdenbos
2. Alan C. Evans
3. Charu C. Aggarwal
4. Ender Konukoglu
5. Chris A. Cocosco
6. Jussi Tohka
7. Mariano Cabezas
8. Ben Glocker
9. Tom Brosch
10. Sébastien Lachapelle

Papers from K. V. Leemput's perspective

Ordered by how strongly the researchers K. V. Leemput trusts endorse each paper. Same corpus, a different order for every researcher.

1. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
2. Automatic anatomical brain MRI segmentation combining label propagation and decision fusion (NeuroImage)
3. Magnetic resonance image tissue classification using a partial volume model. (NeuroImage)
4. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation (IEEE Transactions on Medical Imaging)
5. Consistent image registration (IEEE Transactions on Medical Imaging)
6. Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains (NeuroImage)
7. Automatically parcellating the human cerebral cortex. (Cerebral Cortex)
8. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm (IEEE Transactions on Medical Imaging)
9. ImageNet classification with deep convolutional neural networks
10. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration (NeuroImage)

Their papers

• The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) (2015) — 6,325 citations
• Automated segmentation of multiple sclerosis lesions by model outlier detection (2001) — 555 citations
• SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms (2006) — 337 citations
• A unifying framework for partial volume segmentation of brain MR images (2003) — 337 citations
• A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology (2018) — 522 citations
• High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas (2017) — 426 citations
• A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI (2015) — 1,221 citations
• A Generative Model for Image Segmentation Based on Label Fusion (2010) — 517 citations
• SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms (2006)