Structure Prior Constrained Estimation of Human Cardiac Diffusion Tensors

Chun-Yu Chu , Changyu Sun (1) , Zi-Xiang Kuai , Feng Yang (1) , Yue-Min Zhu (1, 2)

1 MOTIVATE - Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales
2 CREATIS - Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé

The purpose of this study is to increase the accuracy of human cardiac diffusion tensor (DT) estimation in diffusion magnetic resonance imaging (dMRI) with a few diffusion gradient directions. Methods: A structure prior constrained (SPC) method is proposed. The method consists in introducing two regularizers in the conventional nonlinear least squares estimator. The two regularizers penalize the dissimilarity between neighboring DTs and the difference between estimated and prior fiber orientations, respectively. A novel numerical solution is presented to ensure the positive definite estimation. Results: Experiments on ex vivo human cardiac data show that the SPC method is able to well estimate DTs at most voxels and is superiors to the state-of-art methods in terms of the mean errors of principal eigenvector, second eigenvector, helix angle, transverse angle, fractional anisotropy, and mean diffusivity. Conclusion: The SPC method is a practical and reliable alternative to current denoising-or regularization-based methods for the estimation of human cardiac DT. Significance: The SPC method is able to accurately estimate human cardiac DTs in dMRI with a few diffusion gradient directions.

Mots clés: Diffusion tensor estimation; diffusion tensor imaging; fiber orientation constraint; human cardiac; tensor smoothing

Domaines: Imagerie médicale

Chun-Yu Chu, Changyu Sun, Zi-Xiang Kuai, Feng Yang, Yue-Min Zhu. Structure Prior Constrained Estimation of Human Cardiac Diffusion Tensors. IEEE Transactions on Biomedical Engineering, 2019. ⟨hal-02073169⟩