ETD

archivio digitale delle tesi discusse presso l'Università di Pisa

 

Tesi etd-11092018-094823


Tipo di tesi
Tesi di laurea magistrale
Autore
GRASSO, VALERIA
URN
etd-11092018-094823
Titolo
UNSUPERVISED ANALYSIS OF PHASE CONTRAST MRI BY MAXIMALLY STABLE EXTREMAL REGION ALGORITHM FOR PATIENT-SPECIFIC TISSUE CHARACTERIZATION
Struttura
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA BIOMEDICA
Commissione
relatore Prof. Positano, Vincenzo
controrelatore Prof.ssa Santarelli, Maria Filomena
correlatore Prof. Celi, Simona
tutor Ing. Sauvage, Emilie
tutor Ing. Fanni, Benigno Marco
Parole chiave
  • MRI
  • PHASE CONTRAST
  • MSER
  • IMAGE SEGMENTATION
  • QAL METHOD
Data inizio appello
07/12/2018;
Consultabilità
parziale
Data di rilascio
07/12/2021
Riassunto analitico
The thesis is focused on the development of an effective methodology for patient-specific tissue characterization from Phase-Contrast (PC) MR images by flow-area loop (QAL) method. <br>QAL method consists in the analysis of the loop derived from the combination of flow and area time-dependent curves. The slope value obtained by the fitting of the linear portion of the loop represents the Pulse Wave Velocity (PWV). Starting from the PWV estimation, the E value can be inferred.<br>Both flow and area variation can be extracted from PC-MR images. While flow estimation from PC-MR is quite simple, estimation of area is challenging due to small area variations in cardiac cycle in vessels and limited spatial resolution. The thesis works aim to solve this issue by a dedicated image processing approach. To validate the proposed approach, a realistic software phantom was built basing on numeric simulations of fluid dynamic to build “synthetic” PC-MR images. <br>
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