Title :
Tracking tagged MR images with energy-minimizing deformable grids
Author :
Shi, Pengcheng ; Amini, A.A. ; Constable, R. Todd ; Duncan, James S.
Author_Institution :
Yale Univ., New Haven, CT, USA
Abstract :
A framework for automatically tracking tag lines from a sequence of magnetic resonance (MR) images is described. MR tagging is used to create a spatial pattern of varying magnetization so that objects which may otherwise have small intensity variation are textured. The algorithm presented here uses a dynamic programming solution to a variational integral for energy minimization of curves, where the behavior of the curves is controlled by image features and by geometric smoothness.
Keywords :
biomedical NMR; cardiology; medical image processing; algorithm; automatic tracking; cardiac image; dynamic programming solution; energy minimization of curves; energy-minimizing deformable grids; geometric smoothness; image features; magnetic resonance image sequence; spatial pattern; tag lines; tagged MR images; variational integral; varying magnetization; Active contours; Additive noise; Computational modeling; Computer simulation; Energy measurement; Image sequences; Magnetization; Noise robustness; Shape; Tagging;
Conference_Titel :
Bioengineering Conference, 1992., Proceedings of the 1992 Eighteenth IEEE Annual Northeast
Conference_Location :
Kingston, RI, USA
Print_ISBN :
0-7803-0902-2
DOI :
10.1109/NEBC.1992.285985