title: Cardiac fiber tracking using adaptive particle filtering based on tensor rotation invariant in MRI.
abstract: Diffusion magnetic resonance imaging (dMRI) is a non-invasive method currently available for cardiac fiber tracking. However, accurate and efficient cardiac fiber tracking is still a challenge. This paper presents a probabilistic cardiac fiber tracking method based on particle filtering. In this framework, an adaptive sampling technique is presented to describe the posterior distribution of fiber orientations by adjusting the number and status of particles according to the fractional anisotropy of diffusion. An observation model is then proposed to update the weight of particles by rotating diffusion tensor from the primary eigenvector to a given fiber orientation while keeping the shape of the tensor invariant. The results on human cardiac dMRI show that the proposed method is robust to noise and outperforms conventional streamline and particle filtering techniques.
authors: Metislab, LIA CNRS-INSERM, Harbin Institute of Technology, Harbin, People's Republic of China. Department of Information Science & Technology, Heilongjiang University, Harbin, People's Republic of China.
authors: Fanhui
authors: F
authors: Kong
authors: Wanyu
authors: W
authors: Liu
authors: Isabelle E
authors: IE
authors: Magnin
authors: Yuemin
authors: Y
authors: Zhu
mesh_terms: D000465:Algorithms; D016880:Anisotropy; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006321:Heart / Q000502:physiology*; D006331:Heart Diseases / Q000473:pathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D012399:Rotation