Die Autoren Joël Schaerer, Christopher Casta, Jérôme Pousin und Patrick Clarysse fassen in ihrem Artikel den bisherigen Kenntnisstand zur Bildanalyse in der Herz-MRT zusammen und stellen eine neue Methodik für die Segmentierung und Bewegungsverfolgung bei Herzuntersuchungen vor. Dabei greifen sie die Methode der deformierbaren elastischen Vorlage (deformable elastic template) zurück, die sie um eine zeitliche Dimension erweitern. Dadurch soll das Modell robuster und eine gleichzeitige Auswertung aller zeitlichen Frames möglich werden.
Aus dem Abstract:
Strong prior models are a prerequisite for reliable spatio-temporal cardiac image analysis. While several cardiac models have been presented in the past, many of them are either too complex for their parameters to be estimated on the sole basis of MR Images, or overly simplified. In this paper, we present a novel dynamic model, based on the equation of dynamics for elastic materials and on Fourier filtering. The explicit use of dynamics allows us to enforce periodicity and temporal smoothness constraints. We propose an algorithm to solve the continuous dynamical problem associated to numerically adapting the model to the image sequence. Using a simple 1D example, we show how temporal filtering can help removing noise while ensuring the periodicity and smoothness of solutions. The proposed dynamic model is quantitatively evaluated on a database of 15 patients which shows its performance and limitations. Also, the ability of the model to capture cardiac motion is demonstrated on synthetic cardiac sequences. Moreover, existence, uniqueness of the solution and numerical convergence of the algorithm can be demonstrated.
Der Artikel erscheint in der Dezemberausgabe der Zeitschrift Medical Image Analysis (Volume 14, Issue 6, Seiten 738-749).
