Cardiac Displacement Tracking with Data Assimilation Combining a Biomechanical Model and an Automatic Contour Detection
Data assimilation in computational models represents an essential step in building patient-specific simulations. This work aims at circumventing one major bottleneck in the practical use of data assimilation strategies in cardiac applications, namely, the difficulty of formulating and effectively co...
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| Published in | Functional Imaging and Modeling of the Heart Vol. 11504; pp. 405 - 414 |
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| Main Authors | , , , , , , |
| Format | Book Chapter |
| Language | English |
| Published |
Switzerland
Springer International Publishing AG
2019
Springer International Publishing |
| Series | Lecture Notes in Computer Science |
| Subjects | |
| Online Access | Get full text |
| ISBN | 3030219488 9783030219482 |
| ISSN | 0302-9743 1611-3349 |
| DOI | 10.1007/978-3-030-21949-9_44 |
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| Abstract | Data assimilation in computational models represents an essential step in building patient-specific simulations. This work aims at circumventing one major bottleneck in the practical use of data assimilation strategies in cardiac applications, namely, the difficulty of formulating and effectively computing adequate data-fitting term for cardiac imaging such as cine MRI. We here provide a proof-of-concept study of data assimilation based on automatic contour detection. The tissue motion simulated by the data assimilation framework is then assessed with displacements extracted from tagged MRI in six subjects, and the results illustrate the performance of the proposed method, including for circumferential displacements, which are not well extracted from cine MRI alone. |
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| AbstractList | Data assimilation in computational models represents an essential step in building patient-specific simulations. This work aims at circumventing one major bottleneck in the practical use of data assimilation strategies in cardiac applications, namely, the difficulty of formulating and effectively computing adequate data-fitting term for cardiac imaging such as cine MRI. We here provide a proof-of-concept study of data assimilation based on automatic contour detection. The tissue motion simulated by the data assimilation framework is then assessed with displacements extracted from tagged MRI in six subjects, and the results illustrate the performance of the proposed method, including for circumferential displacements, which are not well extracted from cine MRI alone. |
| Author | Groth, Alexandra Weese, Jürgen Tintera, Jaroslav Chabiniok, Radomír Bureau, Gautier Moireau, Philippe Chapelle, Dominique |
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| DOI | 10.1007/978-3-030-21949-9_44 |
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| Editor | Zemzemi, Nejib Vigmond, Edward Ozenne, Valéry Coudière, Yves |
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| RelatedPersons | Kleinberg, Jon M. Hartmanis, Juris Mattern, Friedemann Goos, Gerhard Steffen, Bernhard Kittler, Josef Naor, Moni Mitchell, John C. Terzopoulos, Demetri Pandu Rangan, C. Kanade, Takeo Hutchison, David Tygar, Doug |
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| Snippet | Data assimilation in computational models represents an essential step in building patient-specific simulations. This work aims at circumventing one major... |
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| SubjectTerms | Biophysical heart modeling cine MRI Data assimilation |
| Title | Cardiac Displacement Tracking with Data Assimilation Combining a Biomechanical Model and an Automatic Contour Detection |
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