Abstract
Statistical descriptions of regional wall motion abnormalities of the heart are key to understanding both sub-clinical and clinical progression of dysfunction. In this paper we establish a temporal registration framework of the cardiac cycle to build a spatio-temporal atlas of 300 asymptomatic volunteers and 300 symptomatic patients with myocardial infarction. A finite-element model was customised to each person’s magnetic resonance images with expert-guided semi-automatic spatial and temporal registration of model parameters. A piece-wise linear temporal registration from user-defined key frames was followed by a Fourier series temporal estimation, providing temporal continuity. All spatial and temporal data were then statistically analysed by means of principal component analysis. Results show differences in sphericity, wall thickening and mitral valve dynamics between the two groups. The modes are available from www.cardiacatlas.org . These atlases can be readily applied to abnormality detection and quantification and can also aid in anatomically constrained shape-based algorithms in automatic planning or segmentation.
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Keywords
- Regional Wall Motion
- Regional Wall Motion Abnormality
- Statistical Shape Model
- Nonrigid Image Registration
- Leave Ventricular Model
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Medrano-Gracia, P. et al. (2014). Continuous Spatio-temporal Atlases of the Asymptomatic and Infarcted Hearts. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2013. Lecture Notes in Computer Science, vol 8330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54268-8_17
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DOI: https://doi.org/10.1007/978-3-642-54268-8_17
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