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Course module: 8DM00
8DM00
Front-End Vision and Multiscale Image Analysis
Course info
Course module8DM00
Credits (ECTS)2.5
Category-
Course typeGraduate School
Language of instructionEnglish
Offered byEindhoven University of Technology; Biomedical Engineering; Biomedical Image Analysis;
Is part of-
Contact personprof.dr.ir. B.M. ter Haar Romenij
Telephone4752
E-mailb.m.terhaarromeny@tue.nl
Lecturer(s)
Contactperson for the course
prof.dr.ir. B.M. ter Haar Romenij
Other course modules lecturer
Subject matter expert
prof.dr.ir. B.M. ter Haar Romenij
Other course modules lecturer
Responsible lecturer
prof.dr.ir. B.M. ter Haar Romenij
Feedback and reachability
Other course modules lecturer
Academic year2017
Period
GS2  (13/11/2017 to 04/02/2018)
Starting block
GS2
TimeslotX: no timeslot
Course mode
Fulltime
Remarks-
Registration openfrom 15/06/2017 up to and including 15/10/2017
Application procedureYou apply via OSIRIS Student
Explanation-
Registration using OSIRISYes
Registration open for students from other department(s)Yes
Pre-registrationNo
Waiting listNo
Number of insufficient tests-
Number of groups of preference0
Learning objectives
  • To gain insight in the design of algorithms for biomedical image analysis, and their application;
  • Brain-inspired computing: to gain insight in the mechanisms of the human visual system: physiology, models, basis of ‘deep learning’, and neuro-informatics;
  • Learn to understand how image structure (features, shape, texture, motion and color) are described and detected;
  • Learning how to disseminate a problem in medical image analysis by means of ‘geometric reasoning’;
  • Understanding of adaptive, non-linear image processing techniques to enhance images;
  • Learning to use the discussed algorithms in biomedical applications, such as computer-aided diagnosis and detection, exploiting Mathematica as a design language.
  • Content
    This course discusses and explains modern image processing techniques, with an emphasis on applications in biomedical imaging: tumor detection, blood vessel analysis, brain connectivity, organ segmentation, diabetes screening, etc. The theory and applications are treated with the following strategies:
    • a solid mathematical derivation of all algorithms used;
    • a strong analogy with the presumed working of the human visual system (front-end vision), which we will try to 'mimic' with computer vision algorithms;
    • all theory and computer-laboratory exercises are demonstrated with Mathematica.
    • state-of-the-art theory, discussion of recent literature.
    • applications in biomedical image analysis
    In modern medical image analysis especially the themes of multi-scale (or multi-resolution) and multi-orientation image processing are hot topics. They form the central theme of this course. We will discover that this is an essential and unavoidable consequence of the measurement process, and that it is prominently present in human vision. It has many practical consequences and advantages. Examples are discussed for invariant feature detection, adaptive filtering, detection of optic flow, texture and segmentation, for a range of medical imaging modalities (MRI, CT, Xray, PET, SPECT, ultrasound etc.), in 2D, 3D and 4D.
    Entrance requirements
    You must have completed the final examination bsc program exam
    Entrance requirements tests
    -
    Assumed previous knowledge
    • Some Linear Algebra and Caculus
    • Useful, but not necessary: Imaging techniques
    Previous knowledge can be gained by
    -
    Resources for self study
    -
    Bachelor College or Graduate School
    Graduate School
    URL study guide
    http://www.bmia.bmt.tue.nl/education/courses/FEV/course/index.html
    URL study guide
    http://www.bmia.bmt.tue.nl/education/courses/FEV/course/index.html
    Required materials
    -
    Recommended materials
    "Front-End Vision and Multiscale Image Analysis" by Bart M. ter Haar Romeny, publisher: Springer., available at BME Student Union Protagoras (www.protagoras.tue.nl)
    Further literature is specified on the webpage of the course.
    Instructional modes
    Lecture

    General
    -

    Remark
    1 week hoorcolleges + practicum, 1 week rust, 1 week hoorcolleges + practicum
    Computer practica met Mathematica
    Practical work

    General
    -

    Remark
    1 week hoorcolleges + practicum, 1 week rust, 1 week hoorcolleges + practicum
    Computer practica met Mathematica
    Tests
    Assignment
    Test weight100
    Minimum grade6
    Test typeFinal examination
    Number of opportunities1
    OpportunitiesBlock GS2
    Test duration in minutes-

    Assessment
    -

    Remark
    Answering a series of tasks, which are handed out at the end of the course.

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