TY - JOUR
T1 - Tracking using motion estimation with physically motivated inter-region constraints
AU - Arif, Omar
AU - Sundaramoorthi, Ganesh
AU - Hong, Byungwoo
AU - Yezzi, Anthony J.
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported in part by KAUST Baseline and Visual Computing Center funding, Korea NRF-2010-220-D00078 and NRF-2011-0007898, and the National Science Foundation (NSF) under Grant CCF-1347191 and Grant CMMI-1068624.
PY - 2014/9
Y1 - 2014/9
N2 - We propose a method for tracking structures (e.g., ventricles and myocardium) in cardiac images (e.g., magnetic resonance) by propagating forward in time a previous estimate of the structures using a new physically motivated motion estimation scheme. Our method estimates motion by regularizing only within structures so that differing motions among different structures are not mixed. It simultaneously satisfies the physical constraints at the interface between a fluid and a medium that the normal component of the fluid's motion must match the normal component of the medium's motion and the No-Slip condition, which states that the tangential velocity approaches zero near the interface. We show that these conditions lead to partial differential equations with Robin boundary conditions at the interface, which couple the motion between structures. We show that propagating a segmentation across frames using our motion estimation scheme leads to more accurate segmentation than traditional motion estimation that does not use physical constraints. Our method is suited to interactive segmentation, prominently used in commercial applications for cardiac analysis, where segmentation propagation is used to predict a segmentation in the next frame. We show that our method leads to more accurate predictions than a popular and recent interactive method used in cardiac segmentation. © 2014 IEEE.
AB - We propose a method for tracking structures (e.g., ventricles and myocardium) in cardiac images (e.g., magnetic resonance) by propagating forward in time a previous estimate of the structures using a new physically motivated motion estimation scheme. Our method estimates motion by regularizing only within structures so that differing motions among different structures are not mixed. It simultaneously satisfies the physical constraints at the interface between a fluid and a medium that the normal component of the fluid's motion must match the normal component of the medium's motion and the No-Slip condition, which states that the tangential velocity approaches zero near the interface. We show that these conditions lead to partial differential equations with Robin boundary conditions at the interface, which couple the motion between structures. We show that propagating a segmentation across frames using our motion estimation scheme leads to more accurate segmentation than traditional motion estimation that does not use physical constraints. Our method is suited to interactive segmentation, prominently used in commercial applications for cardiac analysis, where segmentation propagation is used to predict a segmentation in the next frame. We show that our method leads to more accurate predictions than a popular and recent interactive method used in cardiac segmentation. © 2014 IEEE.
UR - http://hdl.handle.net/10754/563740
UR - http://arxiv.org/abs/arXiv:1402.1503v1
UR - http://www.scopus.com/inward/record.url?scp=84906861457&partnerID=8YFLogxK
U2 - 10.1109/TMI.2014.2325040
DO - 10.1109/TMI.2014.2325040
M3 - Article
SN - 0278-0062
VL - 33
SP - 1875
EP - 1889
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
IS - 9
ER -