On the error estimate of the harmonic B _z algorithm in MREIT from noisy magnetic flux field

Abstract

Magnetic resonance electrical impedance tomography (MREIT, for short) is a new medical imaging technique developed recently to visualize the cross-section conductivity of biologic tissues. A new MREIT image reconstruction method called harmonic B _z algorithm was proposed in 2002 with the measurement of B _z that is a single component of an induced magnetic flux density subject to an injection current. The key idea is to solve a nonlinear integral equation by some iteration process. This paper deals with the convergence analysis as well as the error estimate for noisy input data B _z, which is the practical situation for MREIT. By analyzing the iteration process containing the Laplacian operation on the input magnetic field rigorously, the authors give the error estimate for the iterative solution in terms of the noisy level δ and the regularizing scheme for determining ΔB _z approximately from the noisy input data. The regularizing scheme for computing the Laplacian from noisy input data is proposed with error analysis. Our results provide both the theoretical basis and the implementable scheme for evaluating the reconstruction accuracy using harmonic B _z algorithm with practical measurement data containing noise.

Keywords

MREIT / Image reconstruction / Iteration / Error estimate

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