• MRI
• PHASE CONTRAST
• MSER
• IMAGE SEGMENTATION
• QAL METHOD

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.
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.
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.