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Tesi etd-04032018-113737


Thesis type
Tesi di laurea magistrale
Author
FALLO, GIADA
email address
giada.fallo@gmail.com
URN
etd-04032018-113737
Title
Bayesian Optimization for sequence design in quantitative magnetic resonance imaging
Struttura
INFORMATICA
Corso di studi
INFORMATICA
Commissione
relatore Prof. Bacciu, Davide
correlatore Dott. Cisternino, Antonio
controrelatore Prof. Frangioni, Antonio
tutor Dott. Buonincontri, Guido
Parole chiave
  • experimental design
  • quantitative magnetic resonance imaging
  • Gaussian Processes
  • Bayesian Optimization
Data inizio appello
27/04/2018;
Consultabilità
secretata d'ufficio
Data di rilascio
27/04/2021
Riassunto analitico
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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