Biomedical Image Processing / Medical Image Processing
Saeed Kermani; Hamid Abrishami Moghaddam; Mohammad Hasan Moradi
Volume 2, Issue 3 , June 2008, , Pages 215-231
Abstract
This paper presents a new method for quantification analysis of left ventricular performance from the sequences of cardiac magnetic resonance imaging using the three-dimension active mesh model (3DAMM). AMM is composed of topology and geometry of L V and associated elastic material properties. The ...
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This paper presents a new method for quantification analysis of left ventricular performance from the sequences of cardiac magnetic resonance imaging using the three-dimension active mesh model (3DAMM). AMM is composed of topology and geometry of L V and associated elastic material properties. The LV deformation is estimated by fitting the model to the initial sparse displacements which is measured by a new establishing point correspondence procedure. To improve the model, a new shape-based interpolation algorithm was proposed for reconstruction of the intermediate slices. The proposed approach is capable of estimating the displacement field for every desired point of the myocardial wall. Then it leads to measure dense motion field and the local dynamic parameters such as Lagrangian strain. To evaluate the performance of the proposed algorithm, eight image sequences (six real and two synthetic sets) were used and the findings were compared with those reported by other researchers. For synthetic image sequence sets, the mean square error between the length of motion field estimated by the Algorithm and the analytical values was less than 0.5 mm. The results showed that the strain measurements of the normal cases were generally consistent with the previously published values. The results of analysis on a patient data set were also consistent with his clinical evidence. In conclusion, the results demonstrated the superiority of the novel strategy with respect to our formerly presented algorithm. Furthermore, the results are comparable to the current state-of-the-art methods.
