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Modul RO5100-KP08

Medical Robotics (MedRob08)

Duration:


1 Semester
Turnus of offer:


every summer semester
Credit points:


8
Course of studies, specific field and terms:
  • Master Robotics and Autonomous Systems 2019 (optional subject), Elective, 2nd semester
Classes and lectures:
  • Medical Robotics (exercise, 1 SWS)
  • Medical Robotics (lecture, 2 SWS)
  • Inverse Problems in Image Processing (lecture, 2 SWS)
  • Inverse Problems in Image Processing (exercise, 1 SWS)
Workload:
  • 25 Hours exam preparation
  • 90 Hours in-classroom work
  • 125 Hours private studies
Contents of teaching:
  • Introduction to inverse and ill-posed problems on the basis of selected examples (including seismology, impedance tomography, heat conduction, computed tomography, acoustics)
  • Concept of ill-posedness of the inverse problem (Hadamard)
  • Singular value decomposition and generalized inverse
  • Regularization methods (eg Tikhonov, Phillips, Ivanov)
  • Deconvolution
  • Image restoration (deblurring, defocusing)
  • Statistical methods (Bayes, maximum likelihood)
  • Computed Tomography, Magnetic Particle Imaging
Qualification-goals/Competencies:
  • Students are able to explain the concept of ill-posedness of the inverse problem and distinguish given inverse problems regarding good or bad posedness.
  • They are able to formulate inverse problems of mathematical imaging and solve (approximate) with suitable numerical methods.
  • They can assess the condition of a problem and the stability of a method.
  • They master different regularization methods and are able to apply them to practical problems.
  • They know methods to determine a suitable regularization.
  • They can use methods of image reconstruction and restoration on real measurement data.
  • Students are able to explain the concepts of forward and inverse kinematics for the examples of 3-joint and 6-joint robots.
  • They are able to apply methods of medical robot systems and to simple practical applications.
  • Students are able to transfer methods of motion learning to simple practical problems.
  • Students are able to modify templates for dynamic calculations in order to create the calculations for their own constructions.
Grading through:
  • Written or oral exam as announced by the examiner
Responsible for this module:
Teachers:
Literature:
  • Kak and Slaney: Principles of Computerized Tomographic Imaging - SIAM Series 33, New York, 2001
  • Natterer and Wübbeling: Mathematical Methods in Image Reconstruction - SIAM Monographs, New York 2001
  • Bertero and Boccacci: Inverse Problems in Imaging - IoP Press, London, 2002
  • Andreas Rieder: Keine Probleme mit inversen Problemen - Vieweg, Wiesbaden, 2003
  • Buzug: Computed Tomography - Springer, Berlin, 2008
  • J. -C. Latombe: Robot Motion Planning - Dordrecht: Kluwer 1990
  • J.J. Craig: Introduction to Robotics - Pearson Prentice Hall 2002
  • : Vorlesungsskript: Med. Robotics
Language:
  • offered only in English
Notes:

Admission requirements for taking the module:
- None

Admission requirements for participation in module examination(s):
- Successful completion of exercise assignments as specified at the beginning of the semester

Module Exam(s):
- RO5100-L1: Medical Robotics, one oral examination on the contents of both submodules, 100% of the module grade

Letzte Änderung:
25.7.2023