@inproceedings{5ef8416574444401b298f42d9d5458c3,
title = "Cardiac Displacement Tracking with Data Assimilation Combining a Biomechanical Model and an Automatic Contour Detection",
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.",
keywords = "Biophysical heart modeling, Data assimilation, cine MRI",
author = "Radom{\'i}r Chabiniok and Gautier Bureau and Alexandra Groth and Jaroslav Tintera and J{\"u}rgen Weese and Dominique Chapelle and Philippe Moireau",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 10th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2019 ; Conference date: 06-06-2019 Through 08-06-2019",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-21949-9\_44",
language = "English",
isbn = "9783030219482",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "405--414",
editor = "Nejib Zemzemi and Val{\'e}ry Ozenne and Edward Vigmond and Yves Coudi{\`e}re",
booktitle = "Functional Imaging and Modeling of the Heart - 10th International Conference, FIMH 2019, Proceedings",
}