Dosik Hwang

In vivo multi-slice mapping of myelin water content using T2 * decay

Quantitative assessment of the myelin water content in the brain can substantially improve our understanding of white matter diseases such as multiple sclerosis. In this study, in vivo myelin water content was estimated using T(2)* relaxation with multi-slice acquisitions in magnetic resonance imaging (MRI). The main advantages of using T(2)* relaxation are (1) a low specific absorption rate (SAR), which is especially beneficial for imaging at high field strengths, (2) a short first-echo time (approximately 2 ms) and short echo spacing (approximately 1 ms), which allows for the acquisition of multiple sampling points during the fast decay of the myelin water signal, and (3) fast multi-slice acquisitions. High-resolution and multi-slice myelin water fraction (MWF) maps were obtained in a clinically acceptable scan time at 3T. Five healthy adults were scanned with a multi-gradient-echo sequence to acquire T(2)* signal decay data. Images with a dimension of 256x256 at eight slice locations were acquired in 8.5 min with a signal-to-noise ratio (SNR) of 94.8 in the first-echo images. The SNR was further increased by using an anisotropic diffusion filter. Local field gradients (LFG) were estimated from the acquired multi-slice data, and the LFG-induced signal decays were corrected with a first-order approximation of LFG using the sinc function. The corrected T(2)* signal decays were analyzed with a three-pool model to quantify MWF. Our results demonstrate the feasibility of in vivo multi-slice mapping of MWF using multi-compartmental analysis of the T(2)* signal decay.

Influence of wear particle interaction in the sliding interface on friction of metals

Abstract The role of wear particles at the sliding interface on the frictional behavior of metals was investigated with respect to size and agglomeration characteristics using both pin-on-disk and pin-on-reciprocator tribotesters. The wear particle interaction at the sliding interface was monitored using a CCD camera. It was found that the friction coefficient significantly rises once a wear particle is produced and trapped at the interface. Wear particles of soft, ductile metal pairs go through a cycle of agglomeration and breakup, while wear particles of hard material pairs are less likely to agglomerate. The wear particles were smaller for the bidirectional sliding motion compared with those in the unidirectional sliding motion, which resulted in lower friction and wear characteristics. This difference is attributed to the higher probability of particle breakup in bidirectional sliding motion. The frictional behavior was also investigated when metal particles are introduced into the interface of Cu–Cu sliding pair. The friction coefficient increased with the introduction of Ni powder whereas it decreased with the introduction of Al powder. It is concluded from these results that frictional behavior could be altered at will by inserting appropriate particles into the sliding interface.

Improved myelin water quantification using spatially regularized non‐negative least squares algorithm

To improve the myelin water quantification in the brain in the presence of measurement noise and to increase the visibility of small focal lesions in myelin‐water‐fraction (MWF) maps.

Improved estimation of myelin water fraction using complex model fitting

In gradient echo (GRE) imaging, three compartment water modeling (myelin water, axonal water and extracellular water) in white matter has been demonstrated to show different frequency shifts that depend on the relative orientation of fibers and the B0 field. This finding suggests that in GRE-based myelin water imaging, a signal model may need to incorporate frequency offset terms and become a complex-valued model. In the current study, three different signal models and fitting approaches (a magnitude model fitted to magnitude data, a complex model fitted to magnitude data, and a complex model fitted to complex data) were investigated to address the reliability of each model in the estimation of the myelin water signal. For the complex model fitted to complex data, a new fitting approach that does not require background phase removal was proposed. When the three models were compared, the results from the new complex model fitting showed the most stable parameter estimation.

Convergence study of an accelerated ML-EM algorithm using bigger step size

In SPECT/PET, the maximum-likelihood expectation-maximization (ML-EM) algorithm is getting more attention as the speed of computers increases. This is because it can incorporate various physical aspects into the reconstruction process leading to a more accurate reconstruction than other analytical methods such as filtered-backprojection algorithms. However, the convergence rate of the ML-EM algorithm is very slow. Several methods have been developed to speed it up, such as the ordered-subset expectation-maximization (OS-EM) algorithm. Even though OS-type algorithms can bring about significant acceleration in the iterative reconstruction, it is generally believed that ML-EM produces better images, in terms of statistical noise in the reconstruction. In this paper, we present an accelerated ML-EM algorithm with bigger step size and show its convergence characteristics in terms of variance noise and log-likelihood values. We also show some advantages of our method over other accelerating methods using additive forms.

Improvement of signal-to-interference ratio and signal-to-noise ratio in nerve cuff electrode systems

Cuff electrodes are effective for chronic electroneurogram (ENG) recording while minimizing nerve damage. However, the ENG signals are usually contaminated by electromyogram (EMG) activity from the surrounding muscles, stimulus artifacts produced by the electrical stimulation and noise generated in the first stage of the neural signal amplifier. This paper proposed a new cuff electrode to reduce the interference from EMG signals and stimulus artifacts. As a result, when an additional middle electrode was placed at the center of the cuff electrode, a significant improvement in the signal-to-interference ratio was achieved at 11% for the EMG signals and 12% for the stimulus artifacts when compared to a conventional tripolar cuff. Furthermore, a new low-noise amplifier was proposed to improve the signal-to-noise ratio. The circuit was designed based on a noise analysis to minimize the noise, and the results show that the total noise of the amplifier was below 1 μV for a cuff impedance of 1 kΩ and a frequency bandwidth of 300 to 5000 Hz.

Metal Artifact Reduction for Polychromatic X-ray CT Based on a Beam-Hardening Corrector

This paper proposes a new method to correct beam hardening artifacts caused by the presence of metal in polychromatic X-ray computed tomography (CT) without degrading the intact anatomical images. Metal artifacts due to beam-hardening, which are a consequence of X-ray beam polychromaticity, are becoming an increasingly important issue affecting CT scanning as medical implants become more common in a generally aging population. The associated higher-order beam-hardening factors can be corrected via analysis of the mismatch between measured sinogram data and the ideal forward projectors in CT reconstruction by considering the known geometry of high-attenuation objects. Without prior knowledge of the spectrum parameters or energy-dependent attenuation coefficients, the proposed correction allows the background CT image (i.e., the image before its corruption by metal artifacts) to be extracted from the uncorrected CT image. Computer simulations and phantom experiments demonstrate the effectiveness of the proposed method to alleviate beam hardening artifacts.

Susceptibility map-weighted imaging (SMWI) for neuroimaging

To propose a susceptibility map‐weighted imaging (SMWI) method by combining a magnitude image with a quantitative susceptibility mapping (QSM) ‐based weighting factor thereby providing an alternative contrast compared with magnitude image, susceptibility‐weighted imaging, and QSM.

Robust mapping of the myelin water fraction in the presence of noise: Synergic combination of anisotropic diffusion filter and spatially regularized nonnegative least squares algorithm

To improve the mapping of myelin water fraction (MWF) despite the presence of measurement noise, and to increase the visibility of fine structures in MWF maps.

Ring artifact correction using detector line-ratios in computed tomography.

Ring artifacts in computed tomography (CT) images degrade image quality and obscure the true shapes of objects. While several correction methods have been developed, their performances are often task-dependent and not generally applicable. Here, we propose a novel method to reduce ring artifacts by calculating the ratio of adjacent detector elements in the projection data, termed the line-ratio. Our method estimates the sensitivity of each detector element and equalizes them in sinogram space. As a result, the stripe pattern can be effectively removed from sinogram data, thereby also removing ring artifacts from the reconstructed CT image. Numerical simulations were performed to evaluate and compare the performance of our method with that of conventional methods. We also tested our method experimentally and demonstrated that our method has superior performance to other methods.