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A Comparison Framework for Breathing Motion Estimation Methods From 4-D Imaging

Abstract : Motion estimation is an important issue in radia- tion therapy of moving organs. In particular, motion estimates from 4-D imaging can be used to compute the distribution of an absorbed dose during the therapeutic irradiation. We propose a strategy and criteria incorporating spatiotemporal information to evaluate the accuracy of model-based methods capturing breathing motion from 4-D CT images. This evaluation relies on the identification and tracking of landmarks on the 4-D CT images by medical experts. Three different experts selected more than 500 landmarks within 4-D CT images of lungs for three patients. Landmark tracking was performed at four instants of the expi- ration phase. Two metrics are proposed to evaluate the tracking performance of motion-estimation models. The first metric cumu- lates over the four instants the errors on landmark location. The second metric integrates the error over a time interval according to an a priori breathing model for the landmark spatiotemporal trajectory. This latter metric better takes into account the dy- namics of the motion. A second aim of this paper is to estimate the impact of considering several phases of the respiratory cycle as compared to using only the extreme phases (end-inspiration and end-expiration). The accuracy of three motion estimation models (two image registration-based methods and a biomechanical method) is compared through the proposed metrics and statistical tools. This paper points out the interest of taking into account more frames for reliably tracking the respiratory motion.
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Contributor : Pierre-Frédéric Villard Connect in order to contact the contributor
Submitted on : Friday, April 4, 2014 - 8:08:24 AM
Last modification on : Friday, September 10, 2021 - 1:50:11 PM



David Sarrut, Bertrand Delhay, Pierre-Frédéric Villard, Vlad Boldea, Michael Beuve, et al.. A Comparison Framework for Breathing Motion Estimation Methods From 4-D Imaging. IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2007, 26 (12), pp.1636-1648. ⟨10.1109/TMI.2007.901006⟩. ⟨hal-00973183⟩



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