Thesis etd-04032018-113737 |
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Thesis type
Tesi di laurea magistrale
URN
etd-04032018-113737
Thesis title
Bayesian Optimization for sequence design in quantitative magnetic resonance imaging
Department
INFORMATICA
Course of study
INFORMATICA
Supervisors
.
relatore Prof. Bacciu, Davide
correlatore Dott. Cisternino, Antonio
controrelatore Prof. Frangioni, Antonio
tutor Dott. Buonincontri, Guido
correlatore Dott. Cisternino, Antonio
controrelatore Prof. Frangioni, Antonio
tutor Dott. Buonincontri, Guido
Keywords
- Bayesian Optimization
- experimental design
- Gaussian Processes
- quantitative magnetic resonance imaging
Graduation session start date
27/04/2018
Availability
Withheld
Release date
27/04/2088
Abstract (Inglese)
Abstract (Italiano)
The thesis concerns the automatic selection of parameters controlling sequence acquisition in quantitative magnetic resonance imaging. A Bayesian Optimization approach is proposed based on Gaussian Processes. The method has been tested using undersampled acquisition with pseudo-random lists of sequence parameters for the purpose of identifying an optimal schedule to be ultimately used in clinical imaging.
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