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Geometric Tomography - Uniqueness, Statistical Reconstruction and Algorithms
Last Updated: 2026-02-05 15:35:16
Abstract
Self-contained course on the theoretical aspects of the reconstruction of geometric objects from tomographic projection and section data.
Objective
Introduction to geometric tomography and understanding of various theoretical aspects of reconstruction problems.
Content
The 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.
Resources
Literature
R. Gardner: Geometric Tomography F. Natterer: The Mathematics of Computerized Tomography A. Rieder: Keine Probleme mit inversen Problemen
Learning Materials (Links)
- Main link
- Course Website
General Information
- Language
- English
- Levels
- MSC
Examination
- Type
- session examination
- Mode
- oral 20 minutes
Registration & Places
- Max Places
- 25
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Geometric Tomography - Uniqueness, Statistical Reconstruction and Algorithms
The lecturers will communicate the exact lesson times of ONLINE courses.
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2 h weekly |
Offered In
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Electives (For the Master's degree in Applied Mathematics the following additional condition (not manifest in myStudies) must be obeyed: At least 15 of the required 28 credits from core courses and electives must be acquired in areas of applied mathematics and further application-oriented fields.)
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Statistics Master (The following courses belong to the curriculum of the Master's Programme in Statistics. The corresponding credits do not count as external credits even for course units where an enrolment at ETH Zurich is not possible.)
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