CS 736 - Medical Image Computing

Course Description

The implementation-based experiments will rely on C/C++or Matlab environments. As part of the implementation-based experiments the students will be introduced to software tools for medical image processing; examples include popular open-source cross-platform software packages for medical image analysis like the InsightToolkit (www.itk.org), Visualization Toolkit (www.vtk.org),etc., or other tools built using these packages. The course will use simulated and clinical medical image datasets available freely through the Internet from universities or research institutions worldwide.

  • Introduction to imaging modalities, mathematical imaging models, noise and artefact models, sampling, signal modelling and fitting X ray, computed tomography (CT), positron 302225 emission tomography (PET), magnetic resonance imaging (MRI) (including diffusion MRI, functional MRI), ultrasound, microscopy
  • Visualization Methods: sectioning, multimodal images, 302225 overlays, rendering surfaces and volumes, using glyphs Application domains: 3D imaging, PET-CT 302225 imaging, diffusion tensor imaging
  • Image reconstruction Methods: image models, sampling, problem 302225 formulations, algorithms Application domains: MRI, CT 302225
  • Image denoising Methods: Bayesian estimation, nonlinear 302225 smoothing Application domains: MRI, CT, others 302225
  • Image segmentation Methods: clustering, Bayesian estimation, 302225 graph partitioning, classification Application domains: brain, heart, knee, 302225 thorax, abdomen; MRI, CT, ultrasound; cancer imaging
  • Anatomical shape analysis Methods: descriptors, learning shape models, 302225 hypothesis testing Application domains: brain, others 302225
  • Image registration Methods: similarity, transformation 302225 Applications: anatomical atlas, co- 302225 registration, motion correction
  • Content based medical-image retrieval Methods: image descriptors, image similarity 302225 Applications 302225
  • Guide to Medical Image Analysis: Methods and Algorithms Author: Klaus D. Toennies Springer, ISBN 978-1-4471-2751-2
  • Mathematics of Medical Imaging Author: Charles L. Epstein Prentice Hall, 2003. ISBN 97801306754843.
  • Medical Image Reconstruction: A Conceptual Tutorial Author: Gengsheng L. ZengSpringer, 2010. ISBN 978-3-642-05368-9
  • Statistical Models of Shape: Optimisation and Evaluation Authors: Rhodri H. Davies, Carole J. Twining, Chris J. Taylor Springer, 2010. ISBN 978-1-84800-137-4
  • Medical Image Registration Authors: Joseph V. Hajnal, Derek L.G. Hill, David Hawkes CRC Press, 2001. ISBN: 0849300649
  • Reference Notes - Biomedical Signal and Image Processing, Spring 2007 MIT Open Course Ware: Massachusetts Institute of Technology MIT Course Number: HST.582J Authors: Gari Clifford, John Fisher, Julie Greenberg, William Wells ocw.mit.edu
Pre-requisite : N/A
Total credits : 6 credits - Lecture
Type : Department elective
Duration : Full Semester