Robust Estimation of the Apparent Diffusion Coefficient Invariant to Acquisition Noise and Physiological Motion
|Title||Robust Estimation of the Apparent Diffusion Coefficient Invariant to Acquisition Noise and Physiological Motion|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Sanz-Estébanez, S., T. Pieciak, C. Alberola López, and S. Aja-Fernández|
|Journal||Magnetic Resonance Imaging|
|Keywords||Acquisition Noise, Apparent Diffusion Coefficient, Diffusion Weighted Imaging, Multimodal Groupwise Registration, Patient Movement Correction|
In this work we have proposed a methodology for the estimation of the apparent diffusion coefficient in the body from multiple breath hold diffusion weighted images, which is robust to two preeminent confounding factors: noise and motion during acquisition. We have extended a method for the joint groupwise multimodal registration and apparent diffusion coefficient estimation, previously proposed by the authors, in order to correct the bias that arises from the non-Gaussianity of the data and the registration procedure. Results show that the proposed methodology provides a statistically significant improvement both in robustness for displacement fields calculation and in terms of accuracy for the apparent diffusion coefficient estimation as compared with traditional sequential approaches. Reproducibility has also been measured on real data in terms of the distribution of apparent diffusion coefficient differences obtained from different b-values subsets. Our proposal has shown to be able to effectively correct the estimation bias by introducing additional computationally light procedures to the original method, thus providing robust apparent diffusion coefficient maps in the liver and allowing an accurate and reproducible analysis of the tissue.