GPNLPerf: Robust 4d non-rigid motion correction for myocardial perfusion analysis

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Abstract

Since the introduction of wide cone detector systems,CT myocardial perfusion has been an area of increased interest,for which non-rigid registration [NRR] is a key step to further analysis. We propose a novel motion management pipeline for perfusion data,GPNLPerf (Group-wise,non-local,NRR for perfusion analysis) centering on groupwise NRR using non-local spatio-temporal constraints. The proposed pipeline deals with the NRR challenges for 4D perfusion data and results in generating clinically relevant perfusion parameters. We demonstrate results on 9 dynamic perfusion exams comparing results quantitatively with ANTs NRR and also show qualitative results on perfusion maps.

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Thiruvenkadam, S., Shriram, K. S., Patil, B., Nicolas, G., Teisseire, M., Cardon, C., … Mullick, R. (2016). GPNLPerf: Robust 4d non-rigid motion correction for myocardial perfusion analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9902 LNCS, pp. 255–263). Springer Verlag. https://doi.org/10.1007/978-3-319-46726-9_30

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