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Medical imaging processing - 5PMSTIM1

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  • Number of hours

    • Lectures : 6.0
    • Tutorials : 6.0
    • Laboratory works : 8.0
    • Projects : 0
    • Internship : 0
    ECTS : 2.0

Goals

Provide students with an overview of the computational and mathematical methods in medical image processing. The course covers the various modalities of medical imaging data (CT, MRI, PET, and ultrasound). A variety of radiological diagnostic scenarios will be used as examples to motivate the methods. The course has some crossover with other fields of image and signal processing.

Contact Florent CHATELAIN

Content

Description:
This course covers the physics of medical imaging modalities and related techniques, there is also focus on specialized content covering image processing and analysis. It is divided into four parts. The first part discuss the physics of X-ray, CT, PET, MRI, and ultrasound and present the advantages and disadvantages of each imaging modality. The second part focus on Medical Image Registration in which we will study intensity-based methods, including a variety of cost functions (least squares and mutual information), and optimization techniques (fixed-point iteration, gradient descent, etc.) The third part focus on Medical Image Reconstruction in which we study reconstruction techniques for CT (filtered back projection) and MRI (using the FFT). The final part we present some recent state of the art methods using Deep Learning applied to Medical Image Analysis with particular focus on medical image Segmentation for tissue classification.

Content
1. Medical Imaging Modalities: (4h - 2 sessions)
2. Medical Image Registration (2h - 1 sessions)
3. Medical Image Reconstruction (4h - 2 sessions)
4. Application of Deep Learning in Medical Imaging mainly for Segmentation (very general) (2h - 1 sessions)



Prerequisites

Basics of Image Processing including:

  • Spatial Transformations
  • Fourier Series and Fourier Transform
  • Convolution
  • Sampling Theory
  • Aliasing
  • Interpolation
  • Correlation

Tests

Semester 9 - The exam may be taken in french or in english FR EN

CC Labs: 30%
CC two Multi Choice short exam for 10 min : 20%
CT Final Exam: 50%



CC Labs: 30%
CC two Multi Choice short exam for 10 min : 20%
CT Final Exam: 50%

Additional Information

Semester 9 - This course is given in english only EN

Curriculum->Double-Diploma Engineer/Master->Semester 9
Curriculum->Engineering degree->Semester 9

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Date of update September 21, 2021

Université Grenoble Alpes