Resolvability of MUSIC algorithm in solving multiple-dipole biomagnetic localization from spatiotemporal MCG data

Jiange Chen; Noboru Niki; Yutaka Nakaya; Hiroshi Nishitani; Y. M. Kang

doi:10.1117/12.310924

24 June 1998 Resolvability of MUSIC algorithm in solving multiple-dipole biomagnetic localization from spatiotemporal MCG data

Jiange Chen, Noboru Niki, Yutaka Nakaya, Hiroshi Nishitani, Y. M. Kang

Author Affiliations +

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310924
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

The MUSIC (Multiple Signal Classification) algorithm is a recently proposed method in solving multiple dipole localization problem from spatio-temporal magnetocardiograph (MCG) data. There are many factors that may effect the resolvability of MUSIC method in solving MCG inverse problem. For example, the number and space arrangement of sensors, the signal-noise ratio of measurement data, the relative position of dipole to the sensors, the direction of dipole. In the case of multiple dipoles are assumed, the distance and time correlation between the dipoles may take a great effect on the solution accuracy. We need a quantitative method of evaluate the resolvability of MUSIC algorithm. In this paper spherically symmetric conductor model is applied as the forward model. The statistical performance of the MUSIC algorithm is discussed by using the MUSIC error covariance matrix. The Cramer-Rao Lower Bound (CRLB) on localization errors for MCG current source dipole models is presented. The performance of MUSIC algorithm is compared with the ultimate performance corresponding to CRLB. The numerical studies with simulated MCG data are presented in two cases: one dipole is assumed and two dipoles are assumed.

Citation Download Citation

Jiange Chen, Noboru Niki, Yutaka Nakaya, Hiroshi Nishitani, and Y. M. Kang "Resolvability of MUSIC algorithm in solving multiple-dipole biomagnetic localization from spatiotemporal MCG data", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310924

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