Marius Staring

Computer Vision and Pattern Recognition · 2007–2018

A researcher in the Science corpus: 12 papers; trusts 47 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 109 citations into it; #4,398 of 21,575 by trust here, #3,645 by citations
• Radiology, Nuclear Medicine and Imaging — 47 citations into it; #314 of 3,265 by trust here, #362 by citations
• Biomedical Engineering — 27 citations into it; #9,506 of 10,734 by trust here, #3,027 by citations
• Artificial Intelligence — 19 citations into it
• Computational Mechanics — 15 citations into it
• Optimization & Training — 13 citations into it
• Biophysics — 8 citations into it

Whom Marius Staring trusts overall

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

1. Stefan Klein
2. Daniel Rueckert
3. Torsten Rohlfing
4. Philippe Thévenaz
5. Josien P. W. Pluim
6. Michael A. Unser
7. Paul A. Viola
8. Jorge Nocedal
9. James C. Spall
10. Laurent O. Jay

Who trusts Marius Staring overall

1. Stefan Klein
2. Juan Eugenio Iglesias
3. Denis P. Shamonin
4. Shengyu Zhao
5. Andriy Myronenko
6. Xabier Artaechevarria
7. Jiayi Ma
8. Max A. Viergever
9. Aristeidis Sotiras
10. Mert Rory Sabuncu

Papers from Marius Staring's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Fully convolutional networks for semantic segmentation
7. A Stochastic Approximation Method
8. Nonrigid registration using free-form deformations: application to breast MR images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Multi-Atlas-Based Segmentation With Local Decision Fusion—Application to Cardiac and Aortic Segmentation in CT Scans (2009) — 429 citations
• Evaluation of Optimization Methods for Nonrigid Medical Image Registration Using Mutual Information and B-Splines (2007) — 511 citations
• Adaptive Stochastic Gradient Descent Optimisation for Image Registration (2009) — 457 citations
• Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge (2011) — 492 citations
• Nonrigid Image Registration Using Multi-scale 3D Convolutional Neural Networks (2017) — 424 citations
• Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information. (2008) — 460 citations
• Fast parallel image registration on CPU and GPU for diagnostic classification of Alzheimer's disease (2013) — 614 citations
• A deep learning framework for unsupervised affine and deformable image registration (2018) — 778 citations
• End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network (2017) — 485 citations
• A survey of medical image registration - under review (2016) — 286 citations
• SimpleElastix: A User-Friendly, Multi-lingual Library for Medical Image Registration (2016) — 316 citations
• elastix: A Toolbox for Intensity-Based Medical Image Registration (2010) — 4,197 citations