Solving the Magnetocardiography Forward Problem in a Realistic Three-Dimensional Heart-Torso Model

Hu, Zhenghui; Ye, Kaikai; Bai, Mingzhu; Yang, Zekuan; Lin, Qiang

doi:10.1109/access.2021.3098925

Cited by 7 publications

(5 citation statements)

References 28 publications

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“…In real cardiac electrophysiological processes, both primary and secondary currents exist [ 26 ]. FIG.8 (b) shows the simulation result without the secondary current, and FIG.8 (c) shows the results including the primary and secondary currents.…”

Section: Methodsmentioning

confidence: 99%

Vector magnetocardiography using compact optically-pumped magnetometers

Su,

Xu,

et al. 2024

Heliyon

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Section: Methodsmentioning

confidence: 99%

Vector magnetocardiography using compact optically-pumped magnetometers

Su,

Xu,

et al. 2024

Heliyon

Self Cite

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“…The use of a patient-specific torso model is necessary to accurately calculate body surface potentials from myocardial currents [8][9][10]. Since the relative permeability of the human torso does not vary much, not including a torso model incurs fewer errors for forward magnetocardiographic models [11]. For this reason, we will focus on magnetic measurements [12], although an extension to include electric measurements might prove beneficial [11,13,14].…”

Section: State Of the Artmentioning

confidence: 99%

Non-Invasive Electroanatomical Mapping: A State-Space Approach for Myocardial Current Density Estimation

Engelhardt,

Elzenheimer,

Hoffmann

et al. 2023

Bioengineering

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Electroanatomical mapping is a method for creating a model of the electrophysiology of the human heart. Medical professionals routinely locate and ablate the site of origin of cardiac arrhythmias with invasive catheterization. Non-invasive localization takes the form of electrocardiographic (ECG) or magnetocardiographic (MCG) imaging, where the goal is to reconstruct the electrical activity of the human heart. Non-invasive alternatives to catheter electroanatomical mapping would reduce patients’ risks and open new venues for treatment planning and prevention. This work introduces a new system state-based method for estimating the electrical activity of the human heart from MCG measurements. Our model enables arbitrary propagation paths and velocities. A Kalman filter optimally estimates the current densities under the given measurements and model parameters. In an outer optimization loop, these model parameters are then optimized via gradient descent. This paper aims to establish the foundation for future research by providing a detailed mathematical explanation of the algorithm. We demonstrate the feasibility of our method through a simplified one-layer simulation. Our results show that the algorithm can learn the propagation paths from the magnetic measurements. A threshold-based segmentation into healthy and pathological tissue yields a DICE score of 0.84, a recall of 0.77, and a precision of 0.93.

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“…Fourth rank tensors can approximate the diffusivity function from the DW-MRI data guaranteeing the symmetric positive-definite property [75]. Other applications include, X-ray strain imaging of crystals, specifically inverting the transverse ray transform of the projections of the diffraction pattern [51], neutron strain imaging of crystals [51], [86], photoelasticity strain imaging of crystals [87], travel time seismology studying the inner structure of the earth to determine the anisotropic index of refraction of the medium involving the mathematical challenge of determining a symmetric second rank tensor Riemannian metric from its integrals along geodesics [88]- [90], neutron tomography of magnetic vector fields in bulk materials [91], optical tomography of dielectric tensors [92], tomographical imaging of electrical and magnetic sources in brain and heart [93], [94], and tissue magnetic susceptibility tensor MR imaging [95].…”

Section: ) Diffusion Tensor Tomography Magnetic Resonancementioning

confidence: 99%

An Analytical Algorithm for Tensor Tomography From Projections Acquired About Three Axes

Tao

Rohmer

Gullberg

et al. 2022

IEEE Trans. Med. Imaging

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Tensor fields are useful for modeling the structure of biological tissues. The challenge to measure tensor fields involves acquiring sufficient data of scalar measurements that are physically achievable and reconstructing tensors from as few projections as possible for efficient applications in medical imaging. In this paper, we present a filtered back-projection algorithm for the reconstruction of a symmetric second-rank tensor field from directional X-ray projections about three axes. The tensor field is decomposed into a solenoidal and irrotational component, each of three unknowns. Using the Fourier projection theorem, a filtered back-projection algorithm is derived to reconstruct the solenoidal and irrotational components from projections acquired around three axes. A simple illustrative phantom consisting of two spherical shells and a 3D digital cardiac diffusion image obtained from diffusion tensor MRI of an excised human heart are used to simulate directional X-ray projections. The simulations validate the mathematical derivations and demonstrate reasonable noise properties of the algorithm. The decomposition of the tensor field into solenoidal and irrotational components provides insight into the development of algorithms for reconstructing tensor fields with sufficient samples in terms of the type of directional projections and the necessary orbits for the acquisition of the projections of the tensor field. Index Terms-Filtered back-projection algorithm, solenoidal and irrotational components, tensor tomography, directional X-ray projections. I. INTRODUCTION T ENSOR tomography has found important applications in the physical sciences [1], [2], mathematics [3], and medicine [4]. Here we consider the tensor tomography problem as Manuscript

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Solving the Magnetocardiography Forward Problem in a Realistic Three-Dimensional Heart-Torso Model

Cited by 7 publications

References 28 publications

Vector magnetocardiography using compact optically-pumped magnetometers

Vector magnetocardiography using compact optically-pumped magnetometers

Non-Invasive Electroanatomical Mapping: A State-Space Approach for Myocardial Current Density Estimation

An Analytical Algorithm for Tensor Tomography From Projections Acquired About Three Axes

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