GMCAO

GMCAO
Cursus master ingénierie (CMI)Parcours Cursus master ingénierie (CMI) - Informatique, image, réalité virtuelle, interactions et jeux

ComposanteUFR de mathématique et d'informatique

Description

This lecture will present theoretical and practical aspects of 3D modeling, visualization, vision, image processing, and associated algorithms, applied to medical imaging. The practical part will involve training to 3D Slicer, vtk/itk libraries, and opencv.

Compétences requises

Mandatory: algorithmics and programming, python Recommended: GUIs, callback functions, Qt

Compétences visées

After this lecture, the student will be able to

  • segment, reconstruct in 3D, visualize and manipulate 3D scenes of anatomical structures from medical image acquisitions
  • perform operations on the meshes or volume images either interactively or programmatically using vtk/itk and 3D Slicer
  • track the position and orientation of a surgical device or an object in a 3D space

Disciplines

  • Informatique

Syllabus

Introduction to medical images: types, acquisition devices and techniques Basic algorithms and tools for medical imaging: denoising, segmentation, registration, 3D reconstruction, computer vision, object tracking (optical, electromagnetic) and 3D pose estimation Introduction to vtk/itk libraries: usual data structures, notion of filter, algorithms, practice Application of the above notions under the 3D Slicer toolkit: introduction to the GUI, base/component architecture, data manager, 2D-3D visualization. Introduction to 3D Slicer programming: python console, modules / python extensions programming. Refresher on GUIs, callback functions, QT widgets. Vtk objects in 3D Slicer, interaction with volumes (3D images) and models (meshes), interactive points, generated objects (sources), programmatic object modification, application of filters. Opencv. Image-guided surgery: preoperative planning, intraoperative navigation and guidance, geometric optimization, virtual and augmented reality. Theory, examples, and use cases.A project based on a real-life use case will be implemented at the end of the course.

Bibliographie

  • Handbook of Medical Image Computing and Computer Assisted Intervention, The Elsevier and MICCAI Society Book Series, Edited by S. Kevin Zhou, Daniel Rueckert and Gabor Fichtinger, 2020, Academic Press, ISBN 978-0-12-816176-0, https://doi.org/10.1016/C2017-0-04608-6