Magnetic resonance perfusion imaging is a today's very promising method for medicine diagnosis. This thesis deals with a sparse representation of signals, low-rank matrix recovery and compressed sensing, which allows overcoming present physical limitations of magnetic resonance perfusion imaging. Several models for reconstruction of measured perfusion data is introduced and numerical methods for their software implementation, which is an important part of the thesis, is mentioned. Proposed models are verified on simulated and real perfusion data from magnetic resonance.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:231150 |
| Date | January 2014 |
| Creators | Mangová, Marie |
| Contributors | Veselý, Vítězslav, Rajmic, Pavel |
| Publisher | Vysoké učení technické v Brně. Fakulta strojního inženýrství |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
Page generated in 0.0017 seconds