Sung-Uk Zhang

Bio: Sung-Uk Zhang is an academic researcher from Samsung. The author has contributed to research in topics: Fused deposition modeling & Finite element method. The author has an hindex of 9, co-authored 28 publications receiving 261 citations. Previous affiliations of Sung-Uk Zhang include University of Florida & Ulsan National Institute of Science and Technology.

Noise analysis in magnetic resonance electrical impedance tomography at 3 and 11 T field strengths.

Abstract: In magnetic resonance electrical impedance tomography (MREIT), we measure the induced magnetic flux density inside an object subject to an externally injected current. This magnetic flux density is contaminated with noise, which ultimately limits the quality of reconstructed conductivity and current density images. By analysing and experimentally verifying the amount of noise in images gathered from two MREIT systems, we found that a carefully designed MREIT study will be able to reduce noise levels below 0.25 and 0.05 nT at main magnetic field strengths of 3 and 11 T, respectively, at a voxel size of 3 × 3 × 3 mm3. Further noise level reductions can be achieved by optimizing MREIT pulse sequences and using signal averaging. We suggest two different methods to estimate magnetic flux noise levels, and the results are compared to validate the experimental setup of an MREIT system.

High field MREIT: setup and tissue phantom imaging at 11 T.

Abstract: Magnetic resonance electrical impedance tomography (MREIT) has the potential to provide conductivity and current density images with high spatial resolution and accuracy. Recent experimental studies at a field strength of 3 T showed that the spatial resolution of conductivity and current density images may be similar to that of conventional MR images as long as enough current is injected, at least 20 mA when the object being imaged has a size similar to the human head. To apply the MREIT technique to image small conductivity changes using less injection current, we performed MREIT studies at 11 T field strength, where noise levels in measured magnetic flux density data are significantly lower. In this paper we present the experimental results of imaging biological tissues with different conductivity values using MREIT at 11 T. We describe technical difficulties encountered in using high-field MREIT systems and possible solutions. High-field MREIT is suggested as a research tool for obtaining accurate conductivity data from tissue samples and animal subjects.

Temperature-dependent mechanical properties of ABS parts fabricated by fused deposition modeling and vapor smoothing

Abstract: 3D printing technologies have gotten an attention as a viable option for future manufacturing. Among them, FDM is the most popular one because it is inexpensive and can process with multiples materials. Layered surface, that has high roughness, is obtained with the technology due to layer-by-layer based process. This result highly decreases value of the final product. Various methods for postprocessing were proposed to achieve fine surface. Among them, vapor smoothing process is one of powerful methods because of its cost-effectiveness and usefulness. However, this process could affect mechanical property of the printed structure. In this study, we investigated the effect of the vapor smoothing technique with 3D printed structures in terms of thermal-dependent mechanical property. ABS structure was fabricated with FDM and applied into the post-processing. Then, temperature-dependent storage modulus and tan δ of the structure were measured with dynamic mechanical analysis (DMA) in the variation of amount of acetone. The results showed that the process highly affects to the thermal stability. Below 50°C, any differences were not observed. However, lower modulus and higher tan δ were shown in the higher temperature. This experiment provides very useful data for FEM simulation to predict mechanical property of a 3D printed structure.

Imaging and quantification of anomaly volume using an eight-electrode ‘hemiarray’ EIT reconstruction method

Abstract: Electrical impedance tomography (EIT) is particularly well-suited to applications where its portability, rapid acquisition speed and sensitivity give it a practical advantage over other monitoring or imaging systems. An EIT system's patient interface can potentially be adapted to match the target environment, and thereby increase its utility. It may thus be appropriate to use different electrode positions from those conventionally used in EIT in these cases. One application that may require this is the use of EIT on emergency medicine patients; in particular those who have suffered blunt abdominal trauma. In patients who have suffered major trauma, it is desirable to minimize the risk of spinal cord injury by avoiding lifting them. To adapt EIT to this requirement, we devised and evaluated a new electrode topology (the 'hemiarray') which comprises a set of eight electrodes placed only on the subject's anterior surface. Images were obtained using a two-dimensional sensitivity matrix and weighted singular value decomposition reconstruction. The hemiarray method's ability to quantify bleeding was evaluated by comparing its performance with conventional 2D reconstruction methods using data gathered from a saline phantom. We found that without applying corrections to reconstructed images it was possible to estimate blood volume in a two-dimensional hemiarray case with an uncertainty of around 27 ml. In an approximately 3D hemiarray case, volume prediction was possible with a maximum uncertainty of around 38 ml in the centre of the electrode plane. After application of a QI normalizing filter, average uncertainties in a two-dimensional hemiarray case were reduced to about 15 ml. Uncertainties in the approximate 3D case were reduced to about 30 ml.

Extracellular Total Electrolyte Concentration Imaging for Electrical Brain Stimulation (EBS).

Abstract: Techniques for electrical brain stimulation (EBS), in which weak electrical stimulation is applied to the brain, have been extensively studied in various therapeutic brain functional applications. The extracellular fluid in the brain is a complex electrolyte that is composed of different types of ions, such as sodium (Na+), potassium (K+), and calcium (Ca+). Abnormal levels of electrolytes can cause a variety of pathological disorders. In this paper, we present a novel technique to visualize the total electrolyte concentration in the extracellular compartment of biological tissues. The electrical conductivity of biological tissues can be expressed as a product of the concentration and the mobility of the ions. Magnetic resonance electrical impedance tomography (MREIT) investigates the electrical properties in a region of interest (ROI) at low frequencies (below 1 kHz) by injecting currents into the brain region. Combining with diffusion tensor MRI (DT-MRI), we analyze the relation between the concentration of ions and the electrical properties extracted from the magnetic flux density measurements using the MREIT technique. By measuring the magnetic flux density induced by EBS, we propose a fast non-iterative technique to visualize the total extracellular electrolyte concentration (EEC), which is a fundamental component of the conductivity. The proposed technique directly recovers the total EEC distribution associated with the water transport mobility tensor.

Magnetic resonance electrical impedance tomography (MREIT) for high-resolution conductivity imaging

Abstract: Cross-sectional imaging of an electrical conductivity distribution inside the human body has been an active research goal in impedance imaging. By injecting current into an electrically conducting object through surface electrodes, we induce current density and voltage distributions. Based on the fact that these are determined by the conductivity distribution as well as the geometry of the object and the adopted electrode configuration, electrical impedance tomography (EIT) reconstructs cross-sectional conductivity images using measured current-voltage data on the surface. Unfortunately, there exist inherent technical difficulties in EIT. First, the relationship between the boundary current-voltage data and the internal conductivity distribution bears a nonlinearity and low sensitivity, and hence the inverse problem of recovering the conductivity distribution is ill posed. Second, it is difficult to obtain accurate information on the boundary geometry and electrode positions in practice, and the inverse problem is sensitive to these modeling errors as well as measurement artifacts and noise. These result in EIT images with a poor spatial resolution. In order to produce high-resolution conductivity images, magnetic resonance electrical impedance tomography (MREIT) has been lately developed. Noting that injection current produces a magnetic as well as electric field inside the imaging object, we can measure the induced internal magnetic flux density data using an MRI scanner. Utilization of the internal magnetic flux density is the key idea of MREIT to overcome the technical difficulties in EIT. Following original ideas on MREIT in early 1990s, there has been a rapid progress in its theory, algorithm and experimental techniques. The technique has now advanced to the stage of human experiments. Though it is still a few steps away from routine clinical use, its potential is high as a new impedance imaging modality providing conductivity images with a spatial resolution of a few millimeters or less. This paper reviews MREIT from the basics to the most recent research outcomes. Focusing on measurement techniques and experimental methods rather than mathematical issues, we summarize what has been done and what needs to be done. Suggestions for future research directions, possible applications in biomedicine, biology, chemistry and material science are discussed.

Magnetic Resonance Electrical Impedance Tomography (MREIT)

Abstract: Magnetic resonance electrical impedance tomography (MREIT) is a recently developed medical imaging modality visualizing conductivity images of an electrically conducting object. MREIT was motivated by the well-known ill-posedness of the image reconstruction problem of electrical impedance tomography (EIT). Numerous experiences have shown that practically measurable data sets in an EIT system are insufficient for a robust reconstruction of a high-resolution static conductivity image due to its ill-posed nature and the influences of errors in forward modeling. To overcome the inherent ill-posed characteristics of EIT, the MREIT system was proposed in the early 1990s to use the internal data of magnetic flux density ${\bf B}=(B_x,B_y,B_z)$, which is induced by an externally injected current. MREIT uses an MRI scanner as a tool to measure the $z$-component $B_z$ of the magnetic flux density, where $z$ is the axial magnetization direction of the MRI scanner. In 2001, a constructive $B_z$-based MREIT algorithm called the harmonic $B_z$ algorithm was developed and its numerical simulations showed that high-resolution conductivity image reconstructions are possible. This novel algorithm is based on the key observation that the Laplacian $\Delta B_z$ probes changes in the log of the conductivity distribution along any equipotential curve having its tangent to the vector field ${\bf J}\times (0,0,1)$, where ${\bf J}=(J_x,J_y,J_z)$ is the induced current density vector. Since then, imaging techniques in MREIT have advanced rapidly and have now reached the stage of in vivo animal and human experiments. This paper reviews MREIT from its mathematical framework to the most recent human experiment outcomes.

Imposing Dirichlet boundary conditions in the eXtended Finite Element Method

Abstract: The imposition of Dirichlet boundary conditions in a non conformal mesh can be done with the use of Lagrange multipliers. But this leads to an over-constrained problem that produces an unstable solution if the finite element subspace for the Lagrange multipliers field does not satisfy the inf-sup condition. A stabilization technique is presented, with on a parameter depending on the mesh size. A benchmark is resolved to validate the stability of our method.

In Vivo High-ResolutionConductivity Imaging of the Human Leg Using MREIT: The First Human Experiment

Abstract: We present the first in vivo cross-sectional conductivity image of the human leg with 1.7 mm pixel size using the magnetic resonance electrical impedance tomography (MREIT) technique. After a review of its experimental protocol by an Institutional Review Board (IRB), we performed MREIT imaging experiments of four human subjects using a 3 T MRI scanner. Adopting thin and flexible carbon-hydrogel electrodes with a large surface area and good contact, we could inject as much as 9 mA current in a form of 15 ms pulse into the leg without producing a painful sensation and motion artifact. Sequentially injecting two imaging currents in two different directions, we collected induced magnetic flux density data inside the leg. Scaled conductivity images reconstructed by using the single-step harmonic B z algorithm well distinguished different parts of the subcutaneous adipose tissue, muscle, crural fascia, intermuscular septum and bone inside the leg. We could observe spurious noise spikes in the outer layer of the bone primarily due to the MR signal void phenomenon there. Around the fat, the chemical shift of about two pixels occurred obscuring the boundary of the fat region. Future work should include a fat correction method incorporated in the MREIT pulse sequence and improvements in radio-frequency coils and image reconstruction algorithms. Further human imaging experiments are planned and being conducted to produce conductivity images from different parts of the human body.