Paul Yushkevich

Computer Vision and Pattern Recognition · 2003–2016

A researcher in the Science corpus: 9 papers; trusts 12 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

Whom Paul Yushkevich trusts overall

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

  1. Brian B. Avants
  2. Stephen M. Smith
  3. Ross T. Whitaker
  4. Antonio Criminisi
  5. James C. Gee
  6. Trevor J. Hastie
  7. Stanley J. Osher
  8. William E. Lorensen
  9. Guido Gerig
  10. Yoav Benjamini

Who trusts Paul Yushkevich overall

  1. Xiahai Zhuang
  2. Brian B. Avants
  3. Jun Ma
  4. Nicholas J. Tustison
  5. Bilwaj Gaonkar
  6. Hui Zhang
  7. Viren Jain
  8. Ivana Despotovic
  9. Wei Li
  10. Juan Eugenio Iglesias

Papers from Paul Yushkevich's perspective

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

  1. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation (IEEE Transactions on Medical Imaging)
  2. Automatic anatomical brain MRI segmentation combining label propagation and decision fusion (NeuroImage)
  3. Random Forests
  4. Advances in functional and structural MR image analysis and implementation as FSL.
  5. Valmet: A New Validation Tool for Assessing and Improving 3D Object Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  6. ImageNet classification with deep convolutional neural networks
  7. Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains (NeuroImage)
  8. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm (IEEE Transactions on Medical Imaging)
  9. Snakes: Active contour models
  10. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest (NeuroImage)

Their papers