401-4521-70L  Geometric Tomography - Uniqueness, Statistical Reconstruction and Algorithms

SemesterAutumn Semester 2020
LecturersJ. Hörrmann
Periodicitynon-recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
401-4521-70 VGeometric Tomography - Uniqueness, Statistical Reconstruction and Algorithms
The lecturers will communicate the exact lesson times of ONLINE courses.
2 hrs
Thu08:00-10:00ON LI NE »
J. Hörrmann

Catalogue data

AbstractSelf-contained course on the theoretical aspects of the reconstruction of geometric objects from tomographic projection and section data.
ObjectiveIntroduction to geometric tomography and understanding of various theoretical aspects of reconstruction problems.
ContentThe problem of reconstruction of an object from geometric information like X-ray data is a classical inverse problem on the overlap between applied mathematics, statistics, computer science and electrical engineering. We focus on various aspects of the problem in the case of prior shape information on the reconstruction object. We will answer questions on uniqueness of the reconstruction and also cover statistical and algorithmic aspects.
LiteratureR. Gardner: Geometric Tomography
F. Natterer: The Mathematics of Computerized Tomography
A. Rieder: Keine Probleme mit inversen Problemen
Prerequisites / NoticeA sound mathematical background in geometry, analysis and probability is required though a repetition of relevant material will be included. The ability to understand and write mathematical proofs is mandatory.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersJ. Hörrmann
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationoral 20 minutes
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

 
Main linkCourse Website
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

Places25 at the most
Waiting listuntil 25.09.2020

Offered in

ProgrammeSectionType
Data Science MasterCore ElectivesWInformation
Computer Science MasterFocus Elective Courses Theoretical Computer ScienceWInformation
Computer Science MasterElective CoursesWInformation
Computer Science MasterFocus Elective Courses General StudiesWInformation
Mathematics MasterSelection: Probability Theory, StatisticsWInformation
Statistics MasterStatistical and Mathematical CoursesWInformation
Statistics MasterSubject Specific ElectivesWInformation