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Liver 4DMRI: A retrospective image‐based sorting method
Author(s) -
Paganelli Chiara,
Summers Paul,
Bellomi Massimo,
Baroni Guido,
Riboldi Marco
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4927252
Subject(s) - image quality , computer science , artificial intelligence , medical imaging , image registration , computer vision , iterative reconstruction , interquartile range , sorting , gold standard (test) , magnetic resonance imaging , sorting algorithm , nuclear medicine , image (mathematics) , medicine , radiology , mathematics , algorithm , statistics
Purpose: Four‐dimensional magnetic resonance imaging (4DMRI) is an emerging technique in radiotherapy treatment planning for organ motion quantification. In this paper, the authors present a novel 4DMRI retrospective image‐based sorting method, providing reduced motion artifacts than using a standard monodimensional external respiratory surrogate. Methods: Serial interleaved 2D multislice MRI data were acquired from 24 liver cases (6 volunteers + 18 patients) to test the proposed 4DMRI sorting. Image similarity based on mutual information was applied to automatically identify a stable reference phase and sort the image sequence retrospectively, without the use of additional image or surrogate data to describe breathing motion. Results: The image‐based 4DMRI provided a smoother liver profile than that obtained from standard resorting based on an external surrogate. Reduced motion artifacts were observed in image‐based 4DMRI datasets with a fitting error of the liver profile measuring 1.2 ± 0.9 mm (median ± interquartile range) vs 2.1 ± 1.7 mm of the standard method. Conclusions: The authors present a novel methodology to derive a patient‐specific 4DMRI model to describe organ motion due to breathing, with improved image quality in 4D reconstruction.