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A Fourier based algorithm for tracking SPAMM tags in gated magnetic resonance cardiac images
Author(s) -
Zhang Shuqing,
Douglas Margaret A.,
Yaroslavsky Leonid,
Summers Ronald M.,
Dilsizian Vasken,
Fananapazir Lameh,
Bacharach Stephen L.
Publication year - 1996
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 - 10.1118/1.597819
Subject(s) - tracking (education) , noise (video) , algorithm , fourier transform , artificial intelligence , sensitivity (control systems) , computer science , image resolution , computer vision , contrast (vision) , fast fourier transform , physics , mathematics , image (mathematics) , mathematical analysis , psychology , pedagogy , electronic engineering , engineering
A method is described for automatically tracking spatial modulation of magnetization tag lines on gated cardiac images. The method differs from previously reported methods in that it uses Fourier based spatial frequency and phase information to separately track horizontal and vertical tag lines. Use of global information from the frequency spectrum of an entire set of tag lines was hypothesized to result in a robust algorithm with decreased sensitivity to noise. The method was validated in several ways: first, actual tagged cardiac images at end diastole were deformed known amounts, and the algorithm's predictions compared to the known deformations. Second, tagged, gated images of the thigh muscle (assumed to have similar signal to noise characteristics as cardiac images, but to not deform with time) were created. Again the algorithmic predictions could be compared to the known (zero magnitude) deformations and to thigh images which had been artificially deformed. Finally, actual cardiac tagged images were acquired, and comparisons made between manual, visual, determinations of tag line locations, and those predicted by the algorithm. At 0.5 T, the mean bias of the method was <0.34 mm even at large deformations and at late (noisy) times. The standard deviation of the method, estimated from the tagged thigh images, was <0.7 mm even at late times. The method may be expected to have even lower error at higher field strengths.