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Large Diffeomorphic FFD Registration for Motion and Strain Quantification from 3D-US Sequences

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5528))

Abstract

This paper proposes a new registration method for the in vivo quantification of cardiac deformation from a sequence of possibly noisy images. Our algorithm has been applied to 3D ultrasound (3D-US) images, which currently give a reasonable spatial and time resolution, but suffer from significant acquisition noise. Therefore, this modality requires the design of a robust strategy to quantify motion and deformation with the clinical aim of better quantifying cardiac function e.g. in heart failure. In the proposed method, referred to as Large Diffeomorphic Free Form Deformation (LDFFD), the displacement field at each time step is computed from a smooth non-stationary velocity field, thus imposing a coupling between the transformations at successive time steps. Our contribution is to extend this framework to the estimation of motion and deformation in an image sequence. Similarity is captured for the entire image sequence using an extension of the pairwise mutual information metric. The LDFFD algorithm is applied here to recover longitudinal strain curves from healthy and Left-Bundle Branch Block (LBBB) subjects. Strain curves for the healthy subjects are in accordance with the literature. For the LBBB patient, strain quantified before and after Cardiac Resynchronization Therapy show a clear improvement of cardiac function in this subject, in accordance with clinical observations.

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© 2009 Springer-Verlag Berlin Heidelberg

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De Craene, M., Camara, O., Bijnens, B.H., Frangi, A.F. (2009). Large Diffeomorphic FFD Registration for Motion and Strain Quantification from 3D-US Sequences. In: Ayache, N., Delingette, H., Sermesant, M. (eds) Functional Imaging and Modeling of the Heart. FIMH 2009. Lecture Notes in Computer Science, vol 5528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01932-6_47

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  • DOI: https://doi.org/10.1007/978-3-642-01932-6_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01931-9

  • Online ISBN: 978-3-642-01932-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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