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Proceedings Paper

Multifunction extension of simplex optimization method for mutual information-based registration of ultrasound volumes
Author(s): Vladimir Zagrodsky; Raj Shekhar; J. Fredrick Cornhill
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Paper Abstract

Mutual information has been demonstrated to be an accurate and reliable criterion function to perform registration of medical data. Due to speckle noise, ultrasound volumes do not provide a smooth mutual information function. Consequently the optimization technique used must be robust enough to avoid local maxima and converge on the desired global maximum eventually. While the well-known downhill simplex optimization uses a single criterion function, our extension to multi-function optimization uses three criterion functions, namely mutual information computed at three levels of intensity quantization and hence three degrees of noise suppression. Registration was performed with rigid as well as simple non-rigid transformation modes for real-time 3D ultrasound datasets of the left ventricle. Pairs of frames corresponding to the most stationary end- diastolic cardiac phase were chosen, and an initial misalignment was artificially introduced between them. The multi-function simplex optimization reduced the failure rate by a factor of two in comparison to the standard simplex optimization, while the average accuracy for the successful cases was unchanged. A more robust registration resulted form the parallel use of criterion functions. The additional computational cost was negligible, as each of the three implementations of the mutual information used the same joint histogram and required no extra spatial transformation.

Paper Details

Date Published: 3 July 2001
PDF: 8 pages
Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.431124
Show Author Affiliations
Vladimir Zagrodsky, Cleveland Clinic Foundation (United States)
Raj Shekhar, Cleveland Clinic Foundation (United States)
J. Fredrick Cornhill, Cleveland Clinic Foundation (United States)

Published in SPIE Proceedings Vol. 4322:
Medical Imaging 2001: Image Processing
Milan Sonka; Kenneth M. Hanson, Editor(s)

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