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Module guide WS 2018-2022

Module MA5030-KP04, MA5030

Image Registration (Bildregist)

Duration:


1 Semester
Turnus of offer:


every second winter semester
Credit points:


4
Course of studies, specific field and terms:
  • Master MES 2020 (optional subject), mathematics / natural sciences, Arbitrary semester
  • Master Medical Informatics 2019 (optional subject), medical image processing, 1st or 2nd semester
  • Master Medical Informatics 2014 (optional subject), medical image processing, 1st or 2nd semester
  • Master MES 2014 (optional subject), mathematics / natural sciences, 1st semester
  • Master Computer Science 2012 (optional subject), advanced curriculum imaging systems, 2nd or 3rd semester
  • Master MES 2011 (optional subject), mathematics, 1st or 3rd semester
  • Master MES 2011 (advanced curriculum), imaging systems, signal and image processing, 1st or 3rd semester
  • Master CLS 2010 (optional subject), mathematics, 1st or 3rd semester
  • Master Computer Science 2012 (optional subject), advanced curriculum numerical image processing, 2nd or 3rd semester
Classes and lectures:
  • Image Registration (exercise, 1 SWS)
  • Image Registration (lecture, 2 SWS)
Workload:
  • 10 Hours exam preparation
  • 45 Hours in-classroom work
  • 65 Hours private studies and exercises
Contents of teaching:
  • Introduction and basic principles
  • Interpolation
  • Deformation models
  • Landmark-based registration
  • Parametric registration
  • Non-parametric registration and regularization strategies
Qualification-goals/Competencies:
  • Students know the fundamental concepts in image registration.
  • They are able to translate concrete problems into suitable models.
  • They have experience with parametric and non-parametric registration problems.
  • Interdisciplinary qualifications:
  • Students have advanced skills in modeling.
  • They can translate theoretical concepts into practical solutions.
  • They are experienced in implementation.
  • They can think abstractly about practical problems.
Grading through:
  • Written or oral exam as announced by the examiner
Requires:
Responsible for this module:
Teachers:
Literature:
  • Goshtasby: 2D and 3D Image Registration - Wiley 2005
  • Modersitzki: Numerical Methods for Image Registration - Oxford University Press 2004
  • Modersitzki: FAIR: Flexible Algorithms for Image Registration - SIAM 2009
  • Rohr: Landmark-Based Image Analysis - Kluwer 2001
Language:
  • German and English skills required
Notes:

Prerequisites for attending the module:
- None (The competences of the required modules are required for this module, but the modules are not a prerequisite for admission).

Prerequisites for the exam:
- Preliminary examinations can be determined at the beginning of the semester. If preliminary work has been defined, it must have been completed and positively assessed before the initial examination.

Letzte Änderung:
26.11.2019