Article
Radiology, Nuclear Medicine & Medical Imaging
Marlon Perez-Rodas, Rolf Pohmann, Klaus Scheffler, Rahel Heule
Summary: The study investigates the intravascular contribution to the overall balanced SSFP (bSSFP) BOLD effect in human blood at high to ultrahigh field strengths (3 T, 9.4 T, and 14.1 T). The results suggest that intravascular effects need to be considered to better understand the origin of bSSFP BOLD contrast in functional MRI experiments, especially at short TRs. The MIRACLE-R-2 method demonstrated the ability to quantify the apparent decrease in R-2 due to rapid RF refocusing.
MAGNETIC RESONANCE IN MEDICINE
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yicun Wang, Peter van Gelderen, Jacco A. de Zwart, Adrienne E. Campbell-Washburn, Jeff H. Duyn
Summary: Low-field MRI scanners below 1 tesla allow for more widespread diagnostic use, but robust fMRI performance at low field strengths has not been fully demonstrated. This study investigates task-based fMRI at 0.55 tesla, finding robust activation detection but sensitivity to magnetic field variations. Static shimming and postprocessing can partially address these challenges, with standard EPI showing more signal stability compared to transition-band steady-state free precession.
MAGNETIC RESONANCE IN MEDICINE
(2021)
Article
Computer Science, Information Systems
Aixia Yuan, Shaojun Fang, Zhongbao Wang, Hongmei Liu
Summary: A novel multifunctional negative group delay circuit that can realize band-pass, high-pass, and low-pass functions is proposed. Analytical design equations and the effects of element values on circuit performance are provided. Simulation and measurement results confirm the feasibility of the design method.
Article
Radiology, Nuclear Medicine & Medical Imaging
Huilou Liang, Ziyi Pan, Chencan Qian, Chengwen Liu, Kaibao Sun, Dehe Weng, Jing An, Yan Zhuo, Danny J. J. Wang, Hua Guo, Rong Xue
Summary: This study develops a new 2D multi-echo passband balanced SSFP sequence and demonstrates its effectiveness in fast functional brain imaging at 7 T through experiments.
MAGNETIC RESONANCE IN MEDICINE
(2022)
Article
Computer Science, Interdisciplinary Applications
Junjie Zhang, Qing Liu, Haiwen Liu, Dewei Zhang, Dongfang Zhou
Summary: This study introduces a balanced tri-band superconducting band-pass filter using novel double square ring loaded resonators, allowing controllable center frequencies and fractional bandwidths, with enhanced common mode suppression through frequency dispersion technique.
INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Shifeng Li, Leiyang Wang, Bang Wu, Dingyi Guo, Yunfan Li, Yilin Zhao, Gary J. Cheng, Feng Liu
Summary: In this article, a 40-W X-band monolithic GaAs balanced limiter is fabricated using GaAs p-i-n technology. Various techniques such as rounded rectangular p-i-n diode, Lange coupler with widened crossover wires, reasonable thickness I-layer, and optimized isolated terminal resistance are employed to improve the power-handling capability of the limiter. The experimental results demonstrate that the limiter exhibits excellent small-signal performance with an insertion loss of less than 1.2 dB and input/output return losses of less than -20 dB. Moreover, it can handle a maximum power of more than 40 W while maintaining an output power of less than 20 dBm, making it highly suitable for high-power X-band communication systems.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Yifan Zhang, Yongle Wu, Weimin Wang, Jie Yan
Summary: In this paper, common-mode and differential-mode reflectionless balanced bandpass filters using half-wavelength ring resonator are proposed for the first time. By loading absorptive stubs and utilizing specific design techniques, the filters can achieve wideband reflectionless performance and robust common-mode suppression. The simulated and measured results confirm the feasibility of the design theory.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2022)
Article
Computer Science, Information Systems
San-Fu Wang, Hua-Pin Chen, Yitsen Ku, Ming-Xiu Zhong
Summary: This paper presents a method of realizing voltage-mode filter structures through analytical synthesis, which can simultaneously achieve high-pass, band-pass, and low-pass filter functions. By adjusting parameters, resonance frequency and quality factor can be independently adjusted, and a quadrature oscillator can be constructed.
Article
Biophysics
Florian Birk, Felix Glang, Alexander Loktyushin, Christoph Birkl, Philipp Ehses, Klaus Scheffler, Rahel Heule
Summary: The study proposed using neural network to estimate multiple diffusion metrics, utilizing high-resolution bSSFP phase-cycling scheme as NN input and deriving low-resolution target diffusion data through SE-EPI scans. The results showed that the NN predictions were highly reliable in MD for both white matter and gray matter structures, but there was some bias in the dependence on WM anisotropy.
NMR IN BIOMEDICINE
(2022)
Review
Biology
Kimberly B. Weldon, Cheryl A. Olman
Summary: This article discusses the recent achievements and challenges in ultra-high field functional magnetic resonance imaging (fMRI) at the mesoscopic scale. As researchers push to smaller voxel sizes in UHF fMRI, acquisition and analysis decisions may degrade spatial accuracy and must be carefully interpreted. Various acquisition techniques can impact contrast-to-noise ratio and spatial specificity, with acquisition blurring potentially increasing effective voxel size by up to 50% in some dimensions.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2021)
Article
Computer Science, Information Systems
Noy Citron, Eldad Holdengreber, Oz Sorkin, Shmuel E. Schacham, Eliyahu Farber
Summary: This article describes a high-performance S-band cryogenic mixer that combines a 90-degree hybrid coupler, Schottky diodes, band pass and low pass filters. The circuit, implemented based on extensive simulation results, shows excellent performance and can be easily adjusted to different frequency ranges.
Article
Physics, Multidisciplinary
Li Min, Mingyue Pan, Dawei Wang, Zhenhai Luo, Congcai Xu
Summary: This paper proposes a high selectivity balanced tri-band bandpass filter based on SIW technology. The tri-band filtering response and multiple transmission zeros are achieved by merging CQ topology and split topology. The design integrates high selectivity DM transmission and good CM suppression. Experimental results agree well with the simulated results.
FRONTIERS IN PHYSICS
(2022)
Article
Nanoscience & Nanotechnology
Siming Zhao, Baoshun Wang, Ya Huang, Yaqi Zhang, Xueke Wu, Qinyuan Jiang, Di Gao, Fei Wang, Run Li, Yunrui Li, Yanlong Zhao, Jingfa Li, Rufan Zhang
Summary: Dual-band electrochromic (EC) smart windows, which can control indoor temperature by modulating the transmitted light in visible and near-infrared regions, are promising for energy-saving. In this study, a stabilization strategy was proposed to construct a one-dimensional WO3 array-modified PB with porous core-shell structures (PB@WO3). The PB@WO3 showed excellent stability and high coloring efficiency, as well as a dual-band modulation ability under low voltages. The combination of WO3 and PB rendered PB@WO3 with three colors and fast switching speed.
ACS APPLIED NANO MATERIALS
(2023)
Article
Engineering, Electrical & Electronic
Yi Song, Haiwen Liu, Linping Feng, Cheng Guo, Shaoyong Zheng, Zhewang Ma
Summary: In this article, a new class of high-order balanced dual-band high-temperature superconducting bandpass filter based on modified multimode stub-loaded resonators is presented. Theoretical analysis and experimental results show that the filter has good performance.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2022)
Article
Optics
Ali P. Vafa, Parisa Karimi, Amin Khavasi
Summary: The optical high-pass filters introduced in this study utilize total internal reflection and multilayer reflection to enhance resolution for edge detection applications. An optimization algorithm is used to adjust the thickness of layers in the multilayer structure for better approximation of an ideal high-pass filter. These compact and lithography-free devices operate in both 1D and 2D modes, demonstrating edge detection capabilities without the need for a Fourier lens.
OPTICS COMMUNICATIONS
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Huan Minh Luu, Dong-Hyun Kim, Jae-Woong Kim, Seung-Hong Choi, Sung-Hong Park
Summary: The use of artificial neural networks, qMTNet, significantly accelerates data acquisition and fitting for qMT imaging, showing high performance and producing parameters in concordance with ground truth.
MAGNETIC RESONANCE IN MEDICINE
(2021)
Article
Immunology
Jang Hyun Park, Hyun-Jin Kim, Chae Won Kim, Hyeon Cheol Kim, Yujin Jung, Hyun-Soo Lee, Yunah Lee, Young Seok Ju, Ji Eun Oh, Sung-Hong Park, Jeong Ho Lee, Sung Ki Lee, Heung Kyu Lee
Summary: Glioblastoma presents a hypoxic microenvironment that affects gamma delta T cell-mediated antitumor immune responses. The tumor's high demand for oxygen leads to suppression of gamma delta T cell function, which can be alleviated by reducing hypoxia. This study highlights the importance of gamma delta T cells in antitumor immunity against brain tumors.
Article
Radiology, Nuclear Medicine & Medical Imaging
Hyun-Soo Lee, Seon-Ha Hwang, Jaeseok Park, Sung-Hong Park
Summary: The proposed 1sh-CenEPI significantly reduces TE while maintaining similar readout window and providing images comparable to the conventional linear and multishot center-out EPI images. It can be a qualified candidate as a new readout for various magnetization-prepared imaging techniques.
MAGNETIC RESONANCE IN MEDICINE
(2021)
Article
Biophysics
Ki Hwan Kim, Sunghun Seo, Won-Joon Do, Huan Minh Luu, Sung-Hong Park
Summary: The proposed new sampling strategy showed superior performance in various types of MRI imaging, regardless of sampling pattern or datasets, particularly in multicontrast MR imaging and multiple PC-bSSFP imaging.
NMR IN BIOMEDICINE
(2022)
Article
Oncology
Gyu Sang Yoo, Huan Minh Luu, Heejung Kim, Won Park, Hongryull Pyo, Youngyih Han, Ju Young Park, Sung-Hong Park
Summary: The study compares the qualities of synthetic computed tomography (sCT) generated by various deep-learning methods in volumetric modulated arc therapy (VMAT) planning for prostate cancer. The results show that sCT generated from the RgGAN demonstrates the best performance in dosimetric conservation D-98% and D-95% compared to other methodologies.
Article
Radiology, Nuclear Medicine & Medical Imaging
Muhammad Asaduddin, Hong Gee Roh, Hyun Jeong Kim, Eung Yeop Kim, Sung-Hong Park
Summary: This study successfully extracted perfusion maps using deep learning methods from a single dose of contrast agent. Testing showed that U-net with multiple decoders and enhanced encoders performed the best, demonstrating strong agreement between the generated perfusion maps and the ground truth.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Hyun-Seo Ahn, Yujin Jung, Sung-Hong Park
Summary: A new two-compartment renal perfusion model was proposed to calculate glomerular blood transfer rate as a measure of renal function. Using diffusion-weighted arterial spin labeling, it was shown that caffeine significantly increased cortical glomerular blood transfer rate compared to control, indicating its sensitivity in monitoring vasodilation.
MAGNETIC RESONANCE IN MEDICINE
(2022)
Article
Computer Science, Artificial Intelligence
Gyutaek Oh, Hyokyoung Bae, Hyun-Seo Ahn, Sung-Hong Park, Won-Jin Moon, Jong Chul Ye
Summary: Quantitative susceptibility mapping (QSM) is a useful MRI technique for spatially mapping the magnetic susceptibility values of tissues. Deep learning approaches have shown comparable performance to classic methods in QSM reconstruction, with the advantage of faster reconstruction time. However, existing deep learning methods are mostly based on supervised learning and require matched pairs of input phase images and ground-truth maps.
MEDICAL IMAGE ANALYSIS
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Sunghun Seo, Huan Minh Luu, Seung Hong Choi, Sung-Hong Park
Summary: This study presents a model-based deep learning scheme for optimizing sampling patterns in multi-contrast MRI, and compares it with other methods. The results demonstrate the advantages of the proposed scheme in both quantitative and qualitative evaluations, and show that optimizing separate sampling patterns for each contrast is better than optimizing a common sampling pattern. Moreover, the proposed scheme also performs well in a data-driven scenario.
Article
Neurosciences
Jun-Hee Kim, Jae-Geun Im, Sung-Hong Park
Summary: Recent studies have proposed a new method for quantifying CSF pulsation, which successfully detected higher CSF flow during the resting state and typical task states. This method also demonstrated dynamic functional changes in CSF pulsation, showing decreased pulsation during activation-on blocks and increased pulsation during activation-off blocks. Additionally, it significantly correlated with stroke volume measured using PC MRI, providing more accurate pulsatility information and faster results compared to conventional methods.
Article
Radiology, Nuclear Medicine & Medical Imaging
Bomin Kim, Geun Young Lee, Sung-Hong Park
Summary: This study proposed a deep learning model for MR-only ONFH staging, which reduces the additional cost and radiation exposure from the acquisition of CT images. By integrating information from MR images of five different protocols using attention fusion, and using self-supervised learning, the model showed improved performance in ARCO staging. The proposed method has the potential to be used in the diagnosis of other diseases that require staging from multiple MR protocols.
Article
Biophysics
Jun-Hee Kim, Jae-Geun Im, Sung-Hong Park
Summary: This study proposes a new approach to studying the alteration of cerebrospinal fluid (CSF) dynamics in traumatic brain injury (TBI) patients. The findings suggest that the decreased CSF pulsation after TBI could lead to the accumulation of toxic substances in the brain and have an adverse effect on brain function.
NMR IN BIOMEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Eunhyeong Lee, Eun-Ah Lee, Eunji Kong, Haemin Chon, Melissa Llaiqui-Condori, Cheon Ho Park, Beom Yong Park, Nu Ri Kang, Jin-San Yoo, Hyun-Soo Lee, Hyung-Seok Kim, Sung-Hong Park, Seung-Won Choi, Dietmar Vestweber, Jeong Ho Lee, Pilhan Kim, Weon Sup Lee, Injune Kim
Summary: An antibody targeting key signalling pathways has been developed to prevent abnormal blood vessels in brain tumors, thus improving drug delivery into tumor tissues. This study reveals a potential strategy for improving glioblastoma treatment through multiple vascular mechanisms.
EXPERIMENTAL AND MOLECULAR MEDICINE
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Huan Minh Luu, Sung-Hong Park
Summary: This paper presents the author's contribution to the brain tumor segmentation challenge in 2021, with modifications to the nn-UNet model resulting in first place in the final ranking for unseen test data, achieving high dice scores for different tumor regions.
BRAINLESION: GLIOMA, MULTIPLE SCLEROSIS, STROKE AND TRAUMATIC BRAIN INJURIES, BRAINLES 2021, PT II
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Jaa-Yeon Lee, Min A. Yoon, Choong Guen Chee, Jae Hwan Cho, Jin Hoon Park, Sung-Hong Park
Summary: The research aims to accelerate MRI for metal artifact correction in patients with degenerative spine diseases using multi-contrast deep neural networks. It proposes a method to reduce the scan time by generating high SEMAC factor data from low SEMAC factor data. The developed networks provide great performance for correcting metal artifacts with potentially reduced scan time and reasonable quality.
MACHINE LEARNING FOR MEDICAL IMAGE RECONSTRUCTION (MLMIR 2022)
(2022)
Article
Neurosciences
Jose Sanchez-Bornot, Roberto C. Sotero, J. A. Scott Kelso, Ozguer Simsek, Damien Coyle
Summary: This study proposes a multi-penalized state-space model for analyzing unobserved dynamics, using a data-driven regularization method. Novel algorithms are developed to solve the model, and a cross-validation method is introduced to evaluate regularization parameters. The effectiveness of this method is validated through simulations and real data analysis, enabling a more accurate exploration of cognitive brain functions.
