Module RO5100-KP08
Medical Robotics (MedRob08)
Duration
1 Semester
Turnus of offer
every summer semester
Credit points
8
Course of studies, specific fields and terms:
- Master Robotics and Autonomous Systems 2019, optional subject, Elective
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:
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
Last Updated:
25.07.2023