An MRF-based discrete optimization framework for combined DCE-MRI motion correction and pharmacokinetic parameter estimation

Enescu M, Heinrich MP, Hill E, Sharma R, Chappell MA, Schnabel JA (2014)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2014

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Series: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Book Volume: 8677

Pages Range: 73-84

DOI: 10.1007/978-3-319-12289-2_7

Abstract

Dynamic contrast-enhanced MRI (DCE-MRI) images are increasingly used for assessing cancer treatment outcome. These time sequences are typically affected by motion, which causes significant errors in tracer kinetic model analysis. Current intra-sequence registration methods for contrast enhanced data either assume restricted transformations (e.g. translation) or employ continuous optimization, which is prone to local optima. In this work, we propose a new approach to DCE-MRI intra-sequence registration and pharmacokinetic modelling, which is formulated in an MRF optimization framework. The complete 4D graph corresponding to a DCE-MRI sequence is reduced to a concatenation of minimum spanning trees, which can be optimized more efficiently. To address the changes due to contrast, a data cost function which incorporates pharmacokinetic modelling information is formulated. The advantages of this method are demonstrated on 8 DCE-MRI image sequences of patients with advanced rectal tumours, presenting mild to severe motion.

Involved external institutions

University of Oxford GB United Kingdom (GB) Universität zu Lübeck DE Germany (DE)

How to cite

APA:

Enescu, M., Heinrich, M.P., Hill, E., Sharma, R., Chappell, M.A., & Schnabel, J.A. (2014). An MRF-based discrete optimization framework for combined DCE-MRI motion correction and pharmacokinetic parameter estimation. In (pp. 73-84). Springer Verlag.

MLA:

Enescu, Monica, et al. "An MRF-based discrete optimization framework for combined DCE-MRI motion correction and pharmacokinetic parameter estimation." Springer Verlag, 2014. 73-84.

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