Quantification of cardiac function is important for the assessment of abnormalities and response to therapy. We present a method to reconstruct dense cardiac motion from sparse features in tagging MRI, decomposed into solenoidal and irrotational parts using multi-scale Helmholtz decomposition. Reconstruction is based on energy minimization using covariant derivatives exploiting prior knowledge about the motion field. The method is tested on cardiac motion images. Experiments on phantom data show that both covariant derivatives and multi-scale Helmholtz decomposition improve motion field reconstruction.
|Title of host publication||Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges (Second International Workshop, STACOM 2011, Held in Conjunction with MICCAI 2011, Toronto, ON, Canada, September 22, 2011, Revised Selected Papers)|
|Editors||O. Camara, E. Konukoglu, M. Pop, K. Rhode, M. Sermesant, A. Young|
|Place of Publication||Berlin|
|Publication status||Published - 2012|
|Name||Lecture Notes in Computer Science|