@inproceedings{2f99bc100f1f4c889a5fa897c176a88a,
title = "T 1 mapping, AIF and pharmacokinetic parameter extraction from dynamic contrast enhancement MRI data",
abstract = "Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is a sensitive, noninvasive technique for the assessment of microvascular properties of the tissue. Quantitative physiological parameters can be obtained using pharmacokinetic (PK) models that track contrast agents as it passes through the tissue vasculature. Such analysis usually requires prior knowledge of the voxels' T 1 values and of the Arterial Input Function (AIF). Therefore, relaxometry T 1 measurements are usually performed prior to contrast-agent injection and the AIF is manually or automatically extracted from the dynamic data. In this study, a method for a fully automatic analysis of DCE data for joint PK parameters, T 1 mapping and AIF extraction is proposed. Results are shown on simulated data compared to other methods and on data acquired from healthy subjects and patients with Glioblastoma who received anti-angiogenic therapy. The proposed method renders DCE analysis to be robust and easily applicable.",
author = "Gilad Liberman and Yoram Louzoun and Olivier Colliot and \{Ben Bashat\}, Dafna",
year = "2011",
doi = "10.1007/978-3-642-24446-9\_10",
language = "الإنجليزيّة",
isbn = "9783642244452",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "76--83",
booktitle = "Multimodal Brain Image Analysis - First International Workshop, MBIA 2011, Held in Conjunction with MICCAI 2011, Proceedings",
note = "1st International Workshop on Multimodal Brain Image Analysis, MBIA 2011, in Conjunction with the 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011 ; Conference date: 18-09-2011 Through 18-09-2011",
}