Automated Segmentation and Non-Rigid Registration for the Quantitative Evaluation of Myocardial Perfusion from Magnetic Resonance Images

Myocardial perfusion quantification by means of Contrast-Enhanced Cardiac Magnetic Resonance images relies on time consuming frame-by-frame manual tracing of regions of interest. In this Thesis, a novel automated technique for myocardial segmentation and non-rigid registration as a basis for perfusion quantification is presented. The proposed technique is based on three steps: reference frame selection, myocardial segmentation and non-rigid registration. In the first step, the reference frame in which both endo- and epicardial segmentation will be performed is chosen. Endocardial segmentation is achieved by means of a statistical region-based level-set technique followed by a curvature-based regularization motion. Epicardial segmentation is achieved by means of an edge-based level-set technique followed again by a regularization motion. To take into account the changes in position, size and shape of myocardium throughout the sequence due to out of plane respiratory motion, a non-rigid registration algorithm is required. The proposed non-rigid registration scheme consists in a novel multiscale extension of the normalized cross-correlation algorithm in combination with level-set methods. The myocardium is then divided into standard segments. Contrast enhancement curves are computed measuring the mean pixel intensity of each segment over time, and perfusion indices are extracted from each curve. The overall approach has been tested on synthetic and real datasets. For validation purposes, the sequences have been manually traced by an experienced interpreter, and contrast enhancement curves as well as perfusion indices have been computed. Comparisons between automatically extracted and manually obtained contours and enhancement curves showed high inter-technique agreement. Comparisons of perfusion indices computed using both approaches against quantitative coronary angiography and visual interpretation demonstrated that the two technique have similar diagnostic accuracy. In conclusion, the proposed technique allows fast, automated and accurate measurement of intra-myocardial contrast dynamics, and may thus address the strong clinical need for quantitative evaluation of myocardial perfusion.

Measurement of K(892)*0 resonance production in Pb-Pb collisions with the ALICE experiment at the LHC

The analysis of the K(892)*0 resonance production in Pb–Pb collisions at √sNN = 2.76 TeV with the ALICE detector at the LHC is presented. The analysis is motivated by the interest in the measurement of short-lived resonances production that can provide insights on the properties of the medium produced in heavy-ion collisions both during its partonic (Quark-Gluon Plasma) and hadronic phase. This particular analysis exploits particle identification of the ALICE Time-Of-Flight detector. The ALICE experiment is presented, with focus on the performance of the Time-Of-Flight system. The aspects of calibration and data quality controls are discussed in detail, while illustrating the excellent and very stable performance of the system in different collision environments at the LHC. A full analysis of the K*0 resonance production is presented: from the resonance reconstruction to the determination of the efficiency and the systematic uncertainty. The results show that the analysis strategy discussed is a valid tool to measure the K∗0 up to intermediate momenta. Preliminary results on K*0 resonance production at the LHC are presented and confirmed to be a powerful tool to study the physics of ultra-relativistic heavy-ion collisions.