Effects of simulated error-sources on different 3-D CSI-EPT strategies

Three-dimensional contrast source inversion-electrical properties tomography (3-D CSI-EPT) is an iterative reconstruction method that estimates the electrical properties of tissue from transmit field magnetic resonance data. However, in order to bring 3-D CSI-EPT into practice for complex tissue structures and to understand the origin and effect of errors, insight in the sensitivities of reconstruction accuracy to the major error-sources is necessary. In this paper, different strategies for implementing 3-D CSI-EPT, including their iterative structure, are presented, of which the regularized implementation shows the most potential to be used in practice. Moreover, the influence of initialization, noise, stopping criteria, incident fields, B1-maps, transceive phase and domain truncation are discussed. We show that of all these different error-sources, initialization, accurate coil models and domain truncation have the most dramatic effect on electrical properties reconstructions in practice.Imaging- and therapeutic targets in neoplastic and musculoskeletal inflammatory diseas

Limitations of 2-D Field Structure Assumptions in Electrical Properties Tomography and its 3-D CSI-EPT Solution

CSI-EPT is an Electrical Properties Tomography (EPT) reconstruction method that uses a Contrast Source Inversion (CSI) optimization approach to retrieve the conductivity and permittivity profiles of tissue based on -data. The method can handle variations in tissue profiles and was originally implemented for profile reconstructions in the midplane of a birdcage coil, where the RF field exhibits an E-polarized field structure [1]. Recently, CSI-EPT has been extended to a fully 3-D volumetric reconstruction method that is generally applicable (in- or outside the midplane) and no particular field structure or smoothness is assumed [2]. This is a major step towards turning CSI-EPT into a practical reconstruction method. Unfortunately, the computation times significantly increase (hours or even days, depending on the reconstruction domain of interest) and from this point of view a 2-D approach may be preferable. We show, however, that a 2-D approach is only warranted under very specific circumstances and having an E-polarized field structure is a necessary but not sufficient condition. In particular, we show that to obtain accurate tissue reconstructions based on 3-D -data, it is in general necessary to take all electromagnetic field components into account and a 2-D reconstruction approach will lead to reconstruction artefacts

Portable Instrument Panel for Rowers: Krachtsensor

Dit verslag beschrijft het onderzoeken en ontwerpen van een krachtsensor voor een roeiboot. Het geleverde ontwerp wordt gezien als onderdeel van een totaalsysteem om het vermogen van een roeier te meten. Keuzes gemaakt in deze thesis zijn gemaakt met dit totaalsysteem in het achterhoofd gehouden. Na een korte blik op verschillende bestaande systemen en principes om kracht te meten, wordt een uitgebreider onderzoek gedaan naar een systeem berustend op de volgende principes: optisch d.m.v. een fibre Bragg grating (FBG), optisch d.m.v. een lichtbron met doelwit en capacitief. Op basis van een PSD is een sensor ontwikkeld. Hiermee is een krachtmeetsysteem ontworpen en een prototype gemaakt. Deze voldoet nog niet aan de vooraf gestelde eisen. De sensor ondervindt nog grote variatie binnen de behaalde meetresultaten waardoor het nog niet mogelijk is om een nauwkeurige conversiefactor, om de buiging van de paal naar kracht te converteren, te bepalen. Op dit moment is het meest nauwkeurige resultaat een conversiefactor van 8,69 newton per verplaatsing met een onnauwkeurigheid van 2,66%. De verplaatsing heeft een afwijking van het gemiddelde van 0,42%.Electronic InstrumentationMicroelectronics & Computer EngineeringElectrical Engineering, Mathematics and Computer Scienc

Sensitivity of 3-D CSI-EPT Reconstructions to Modelled EM Field Variations and Object Truncation

Model-based electrical properties tomography (EPT; [1,2]) reconstruction with 3-D Contrast Source Inversion-EPT (CSI-EPT; [3,4]) has high potential, but is inherently sensitive to small errors in the model used. Here we assess its sensitivity to errors in the incident electromagnetic (EM) fields due to coupling of the coil to the sample (loading effect), errors in the total EM fields due to errors in mapping methods, and the effect of different object truncations

Limitations of 2-D Field Structure Assumptions in Electrical Properties Tomography and its 3-D CSI-EPT Solution

CSI-EPT is an Electrical Properties Tomography (EPT) reconstruction method that uses a Contrast Source Inversion (CSI) optimization approach to retrieve the conductivity and permittivity profiles of tissue based on -data. The method can handle variations in tissue profiles and was originally implemented for profile reconstructions in the midplane of a birdcage coil, where the RF field exhibits an E-polarized field structure [1]. Recently, CSI-EPT has been extended to a fully 3-D volumetric reconstruction method that is generally applicable (in- or outside the midplane) and no particular field structure or smoothness is assumed [2]. This is a major step towards turning CSI-EPT into a practical reconstruction method. Unfortunately, the computation times significantly increase (hours or even days, depending on the reconstruction domain of interest) and from this point of view a 2-D approach may be preferable. We show, however, that a 2-D approach is only warranted under very specific circumstances and having an E-polarized field structure is a necessary but not sufficient condition. In particular, we show that to obtain accurate tissue reconstructions based on 3-D -data, it is in general necessary to take all electromagnetic field components into account and a 2-D reconstruction approach will lead to reconstruction artefacts.Circuits and System

Transverse-EPT: A local first order electrical properties tomography approach not requiring estimation of the incident fields

A new local method for magnetic resonance electrical properties tomography (EPT), dubbed transverse-EPT (T-EPT), is introduced. This approach iteratively optimizes the dielectric properties (conductivity and permittivity) and the z-component of the electric field strength, exploiting the locally E-polarized field structure typically present in the midplane of a birdcage radiofrequency (RF) coil. In contrast to conventional Helmholtz-based EPT, T-EPT does not impose homogeneity assumptions on the object and requires only first order differentiation operators, which makes the method more accurate near tissue boundaries and more noise robust. Additionally, in contrast to integral equation-based approaches, estimation of the incident fields is not required. The EPT approach is derived from Maxwell’s equations and evaluated on simulated data of a realistic tuned RF coil model to demonstrate its potential.</p

Sensitivity of 3-D CSI-EPT Reconstructions to Modelled EM Field Variations and Object Truncation

Model-based electrical properties tomography (EPT; [1,2]) reconstruction with 3-D Contrast Source Inversion-EPT (CSI-EPT; [3,4]) has high potential, but is inherently sensitive to small errors in the model used. Here we assess its sensitivity to errors in the incident electromagnetic (EM) fields due to coupling of the coil to the sample (loading effect), errors in the total EM fields due to errors in mapping methods, and the effect of different object truncations.Circuits and System

Transverse-EPT: A local first order electrical properties tomography approach not requiring estimation of the incident fields

A new local method for magnetic resonance electrical properties tomography (EPT), dubbed transverse-EPT (T-EPT), is introduced. This approach iteratively optimizes the dielectric properties (conductivity and permittivity) and the z-component of the electric field strength, exploiting the locally E-polarized field structure typically present in the midplane of a birdcage radiofrequency (RF) coil. In contrast to conventional Helmholtz-based EPT, T-EPT does not impose homogeneity assumptions on the object, and requires only first order differences, which makes the method more accurate near tissue boundaries and more noise robust. Additionally, in contrast to integral equation-based approaches, estimation of the incident fields is not required. The EPT approach is derived from Maxwell's equations and evaluated on simulated data of a realistic tuned RF coil model to demonstrate its potential.Circuits and SystemsElectrical Engineering, Mathematics and Computer Scienc

Developments in electrical-property tomography based on the contrast-source inversion method

The main objective of electrical-property tomography (EPT) is to retrieve dielectric tissue parameters from B 1 + data as measured by a magnetic-resonance (MR) scanner. This is a so-called hybrid inverse problem in which data are defined inside the reconstruction domain of interest. In this paper, we discuss recent and new developments in EPT based on the contrast-source inversion (CSI) method. After a short review of the basics of this method, two- and three-dimensional implementations of CSI-EPT are presented along with a very efficient variant of 2D CSI-EPT called first-order induced current EPT (foIC-EPT). Practical implementation issues that arise when applying the method to measured data are addressed as well, and the limitations of a two-dimensional approach are extensively discussed. Tissue-parameter reconstructions of an anatomically correct male head model illustrate the performance of two- and three-dimensional CSI-EPT. We show that 2D implementation only produces reliable reconstructions under very special circumstances, while accurate reconstructions can be obtained with 3D CSI-EPT. Circuits and System

Electrical Properties Tomography: A Methodological Review

Electrical properties tomography (EPT) is an imaging method that uses a magnetic resonance (MR) system to non-invasively determine the spatial distribution of the conductivity and permittivity of the imaged object. This manuscript starts by providing clear definitions about the data required for, and acquired in, EPT, followed by comprehensively formulating the physical equations underlying a large number of analytical EPT techniques. This thorough mathematical overview of EPT harmonizes several EPT techniques in a single type of formulation and gives insight into how they act on the data and what their data requirements are. Furthermore, the review describes machine learning-based algorithms. Matlab code of several differential and iterative integral methods is available upon request