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Title: Quantitative functional brain imaging with Positron Emission Tomography and irreversible tracers
Author: Veronese, Mattia
Awarding Body: King's College London (University of London)
Current Institution: King's College London (University of London)
Date of Award: 2013
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This thesis presents SAIF, (Spectral Analysis with Iterative Filter), a SA-based method for the quantification of PET data investigated with irreversible-uptake tracers. SAIF has been designed in order to maintain the main advantages of SA but providing a superior robustness to measurement noise. The final aim was to create a reliable and flexible PET quantification tool, offering a valid alternative to standard methodologies for functional quantitative imaging with PET and irreversible tracers.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available