2026-04-14T19:29:47Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/313822025-02-21T12:26:06Zcom_10324_1191com_10324_931com_10324_894col_10324_1379

Sanz Estébanez, Santiago Rodrigo Pieciak, Tomász Alberola López, Carlos Aja Fernández, Santiago 2018-09-03T20:08:58Z 2018-09-03T20:08:58Z 2018 Magnetic Resonance Imaging, Julio 2018 http://uvadoc.uva.es/handle/10324/31382 Purpose: In this work we have proposed a methodology for the estimation of the apparent diffusion coeffcient in the body from multiple breath hold diffusion weighted images, which is robust to two preeminent confounding factors: noise and motion during acquisition. Methods: 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: Results show that the proposed methodology provides a statistically signi ficant improvement both in robustness for displacement elds 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. Conclusions: 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. application/pdf spa info:eu-repo/semantics/restrictedAccess http://creativecommons.org/licenses/by/4.0/ Attribution 4.0 International Robust Estimation of the Apparent Diffusion Coefficient Invariant to Acquisition Noise and Physiological Motion info:eu-repo/semantics/article SI