This is a tutorial for anyone who wants to learn Medical Image Registration

The tutorial is divided into four parts:

• Pre / Pos - Processing:

  • Intensity Normalization
  • Space Normalization
  • Brain Extraction
  • Validation

• Registration with Classical Methodologies:

  • AIR
  • Demons(Diffeomorfic, Mutual Information )
  • DRAMMS
  • DROP
  • Dartel
  • FLIRT
  • FNIRT
  • SyN

• Registration with Deep Learning

  • Learning to use Autoencoders (Autoencoder (shallow), Deep Autoencoder and Convolutional Autoencoder)

• Interesting Platforms to Learn and Use

  • ANTs
  • NiftyReg
  • Freesurfer
  • 3D Slicer
  • BIAL
  • MedInria
  • Medpy
  • Nipype
  • FSL

Paper Sibgrapi (2018) -> A Practical Review on Medical Image Registration: from Rigid to Deep Learning based Approaches

http://sibgrapi.sid.inpe.br/col/sid.inpe.br/sibgrapi/2018/09.11.00.20/doc/Paper%20ID%20Tutorial-1.pdf

Slides Tutorial:

Part 1: http://www.imago.ufpr.br/sibgrapi2018/PART1-TUTORIAL_FUNDAMENTAL.pdf.pdf

Part 2 and 3: http://www.imago.ufpr.br/sibgrapi2018/tutorials.php

Tutorial Videos:

https://www.youtube.com/playlist?list=PLqoEuqQOzdkthOTuuXq4Ect4AS90lrsM5

Coming soon:

1. Undergraduate thesis: A Practical Review on Medical Image Registration

Do not forget to cite the article and this content!:wink:

For more information visit:

Group for Innovation Based on Images and Signals (GIBIS): http://gibis.unifesp.br/

Universidade Federal de São Paulo (UNIFESP) - Instituto de Ciência e Tecnologia (ICT) - BRASIL

http://www.unifesp.br/campus/sjc/

AUTHOR: NaTaNdRaDe