2007 IEEE 11th International Conference on Computer Vision 2007
DOI: 10.1109/iccv.2007.4409133
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Bilinear Models for Spatio-Temporal Point Distribution Analysis: Application to Extrapolation of Whole Heart Cardiac Dynamics

Abstract: In this work we introduce the usage of bilinear models as a means of factorising the shape variation induced by subject variability and the contraction of the human heart. We show that it is feasible to reconstruct the shape of the heart at a certain point in the cardiac cycle if we are given a small number of shapes representing the same heart at different points in the same cycle, using the bilinear model. Depending on pathology and the ratios between healthy and pathological hearts in the training set, RMS … Show more

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Cited by 12 publications
(26 citation statements)
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“…The resulting dataset consisted of 15 image volumes (temporal phases) obtained using retrospective ECG gating [8] with voxel dimensions of 0.4×0.4×2.0 mm 3 per subject. For more details about the data set and the segmentation method, the reader can refer to [9,10].…”
Section: Methodsmentioning
confidence: 99%
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“…The resulting dataset consisted of 15 image volumes (temporal phases) obtained using retrospective ECG gating [8] with voxel dimensions of 0.4×0.4×2.0 mm 3 per subject. For more details about the data set and the segmentation method, the reader can refer to [9,10].…”
Section: Methodsmentioning
confidence: 99%
“…Please, see Hoogendoorn et al [9,10] for further details. Bilinear models cannot be computed from a single individual's data.…”
Section: Bilinear Cardiac Motion Modelingmentioning
confidence: 97%
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“…To the best of our knowledge, our previous work (Hoogendoorn et al 2007) was the first to model individual and temporal variations of cardiac shape as two different sources of variability within the same set of data. Before, inter-subject variation and dynamics were not decoupled at all Mitchell et al 2002;Hamarneh and Gustavsson 2004).…”
Section: Statistical Shape Models and Timementioning
confidence: 99%