Author name cluster

Jongho Lee

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26 papers

2 author rows

YNICL Journal 2025 Journal Article

Association of iron deposition in MS lesion with remyelination capacity using susceptibility source separation MRI

Hyeong-Geol Shin
Woojun Kim
Jung Hwan Lee
Hyun-soo Lee
Yoonho Nam
Jiwoong Kim
Xu Li
Peter C.M. van Zijl

OBJECTIVES: signals within MS lesions using χ-separation and evaluate the association between lesional iron and remyelination capability. METHODS: signals. RESULTS: myelin signals (P < 0.001). After adjustment, lesions with early HPS demonstrated an annual loss in myelin signal (-1.94 ppb/year), whereas those without early HPS exhibited annual recovery (+0.66 ppb/year). Participants with confirmed disability improvement (CDI) had fewer HPS-positive lesions at baseline than those without CDI (P < 0.001). CONCLUSION: The presence of HPS is associated with impaired remyelination capacity and a lack of disease improvement in pwMS. Identifying HPS may help demarcate lesions more amenable to myelin repair therapies.

YNIMG Journal 2025 Journal Article

In-vivo high-resolution χ-separation at 7T

Jiye Kim
MinJun Kim
Sooyeon Ji
Kyeongseon Min
Hwihun Jeong
Hyeong-Geol Shin
Chungseok Oh
Robert J. Fox

A recently introduced quantitative susceptibility mapping (QSM) technique, χ-separation, offers the capability to separate paramagnetic (χpara ) and diamagnetic (χdia ) susceptibility distribution within the brain. In-vivo high-resolution mapping of iron and myelin distribution, estimated by χ-separation, could provide a deeper understanding of brain substructures, assisting the investigation of their functions and alterations. This can be achieved using 7T MRI, which benefits from a high signal-to-noise ratio and susceptibility effects. However, applying χ-separation at 7T presents difficulties due to the requirement of an R2 map, coupled with issues such as high specific absorption rate (SAR), large B1 transmit field inhomogeneities, and prolonged scan time. To address these challenges, we developed a novel deep neural network, R2PRIMEnet7T, designed to convert a 7T R2* map into a 3T R2′ map. Building on this development, we present a new pipeline for χ-separation at 7T, enabling us to generate high-resolution χ-separation maps from multi-echo gradient-echo data. The proposed method is compared with alternative pipelines, such as an end-to-end network and linearly-scaled R2′, and is validated against χ-separation maps at 3T, demonstrating its accuracy. The 7T χ-separation maps generated by the proposed method exhibit similar contrasts to those from 3T, while 7T high-resolution maps offer enhanced clarity and detail. Quantitative analysis confirms that the proposed method surpasses the alternative pipelines. The proposed method results well delineate the detailed brain structures associated with iron and myelin. This new pipeline holds promise for analyzing iron and myelin concentration changes in various neurodegenerative diseases through precise structural examination.

YNIMG Journal 2025 Journal Article

Resolution generalization of deep learning-based dipole inversion networks for QSM

Sooyeon Ji
MinJun Kim
Jongho Lee
Hyeong-Geol Shin

Deep learning-based dipole inversion networks for quantitative susceptibility mapping (QSM) display low performance when test data resolution is different from network-trained data resolution. While several approaches were proposed to enhance the dipole inversion networks’ resolution generalizability, they modify network architecture or parameter, limiting direct application to existing pre-trained dipole inversion networks. This study presents a novel pipeline that enables pre-trained dipole inversion networks to reconstruct QSM from input local field maps of various resolutions. The developed pipeline consisted of four steps. (ⅰ) The local field map was re-sampled at multiple different spatial locations, generating multiple local field maps at network-trained resolution. (ⅱ) The re-sampled local field maps were inferred through the network, generating QSM maps. (ⅲ) These QSM maps were combined, and then (ⅳ) compensated for systematic errors, introduced by the previous re-sampling and combining process, by “dipole compensation”. The performance of the proposed pipeline was compared with two alternative pipelines using the same network: interpolating the input data to the trained resolution prior to inference (interpolation pipeline), and naïvely inferencing (naïve-input pipeline). Through qualitative and quantitative evaluations, we demonstrate that the proposed pipeline displays superior performance compared to the alternative pipelines. Specifically, when a local field map of 1 mm3 resolution was tested using QSMnet pre-trained at 1. 5 mm3 resolution, the proposed pipeline outperformed the two alternative pipelines (NRMSE: 43. 1/49. 3/56. 0, SSIM: 0. 933/0. 910/0. 920, PSNR: 47. 1/46. 0/44. 8, HFEN: 39. 9/40. 8/48. 0 for proposed/interpolation/naïve-input pipeline). This study provides a promising solution for enhancing the generalizability of pre-trained dipole inversion networks to different input data resolutions, widening their applications in clinical settings.

AAAI Conference 2025 Conference Paper

RTP-LX: Can LLMs Evaluate Toxicity in Multilingual Scenarios?

Adrian de Wynter
Ishaan Watts
Tua Wongsangaroonsri
Minghui Zhang
Noura Farra
Nektar Ege Altıntoprak
Lena Baur
Samantha Claudet

Large language models (LLMs) and small language models (SLMs) are being adopted at remarkable speed, although their safety still remains a serious concern. With the advent of multilingual S/LLMs, the question now becomes a matter of scale: can we expand multilingual safety evaluations of these models with the same velocity at which they are deployed? To this end, we introduce RTP-LX, a human-transcreated and human-annotated corpus of toxic prompts and outputs in 28 languages. RTP-LX follows participatory design practices, and a portion of the corpus is especially designed to detect culturally-specific toxic language. We evaluate 10 S/LLMs on their ability to detect toxic content in a culturally-sensitive, multilingual scenario. We find that, although they typically score acceptably in terms of accuracy, they have low agreement with human judges when scoring holistically the toxicity of a prompt; and have difficulty discerning harm in context-dependent scenarios, particularly with subtle-yet-harmful content (e.g. microaggressions, bias). We release this dataset to contribute to further reduce harmful uses of these models and improve their safe deployment.

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YNIMG Journal 2025 Journal Article

χ-separation insights into whole-brain characterization of age-related patterns of susceptibility in healthy aging

Simi Zhou
Yoshitaka Bito
Hiroyuki Kameda
Yohei Ikebe
Yukie Shimizu
Noriyuki Fujima
Taisuke Harada
Naoya Kinota

Quantitative Susceptibility Mapping (QSM) enables noninvasive assessment of brain tissue composition, but conventional approaches provide only a composite measure that merges paramagnetic and diamagnetic contributions, limiting biological specificity. Recent advances in χ-separation overcome this limitation by separating χ-paramagnetic (χ-para) and χ-diamagnetic (χ-dia) components within a single voxel. This study aimed to comprehensively characterize age-related trajectories of paramagnetic and diamagnetic susceptibility changes across the adult lifespan, thereby establishing normative reference patterns for interpreting neuropathological alterations. A total of 131 healthy adults (62 males, 69 females; age 21-89 years) underwent multi-echo gradient echo. χ-separation was applied to generate χ-para, χ-dia, and total susceptibility (χ-tot) maps. Median susceptibility was extracted using a customized 69-region parcellation (cortical, subcortical, and white matter regions). Age effects were assessed with linear and non-linear regression analyses. χ-para exhibited positive linear, quadratic, or exponential associations with aging in caudate, putamen, substantia nigra (SN), red nucleus (RN), subthalamic nucleus (STN), thalamic subdivisions, superior frontal areas around the primary motor cortex, parietal, temporal, occipital, limbic, and insular cortices, splenium of corpus callosum (CC), posterior limb of internal capsule (PLIC,) and anterior of corona radiata (CR). |χ-dia| showed negative linear or quadratic declines in genu, body, and splenium of CC, PLIC, anterior and posterior of CR, posterior thalamic radiation, SN, RN, STN, ventral pallidum, pulvinar, and superior frontal regions. By explicitly separating paramagnetic and diamagnetic components, χ-separation provided novel insights into microstructural age-dependent trajectories, offering biologically specific normative references for iron accumulation and myelin decline, with implications for studying neurodegenerative disorders.

IJCAI Conference 2024 Conference Paper

HyQ: Hardware-Friendly Post-Training Quantization for CNN-Transformer Hybrid Networks

Nam Joon Kim
Jongho Lee
Hyun Kim

Hybrid models that combine CNNs and ViTs have recently emerged as state-of-the-art computer vision models. To efficiently deploy these hybrid models on resource-constrained mobile/edge devices, quantization is emerging as a promising solution. However, post-training quantization (PTQ), which does not require retraining or labeled data, has not been extensively studied for hybrid models. In this study, we propose a novel PTQ technique specialized for CNN-transformer hybrid models by considering the hardware design of hybrid models on AI accelerators such as GPUs and FPGAs. First, we introduce quantization-aware distribution scaling to address the large outliers caused by inter-channel variance in convolution layers. Furthermore, in the transformer block, we propose approximating the integer-only softmax with a linear function. This approach allows us to avoid costly FP32/INT32 multiplications, resulting in more efficient computations. Experimental results show that the proposed quantization method with INT8 precision demonstrated a 0. 39% accuracy drop compared with the FP32 baseline on MobileViT-s with the ImageNet-1k dataset. Furthermore, when implemented on the FPGA platform, the proposed linear softmax achieved significant resource savings, reducing the look-up table and flip-flop usage by 1. 8 ~ 2. 1x and 1. 3 ~ 1. 9x, respectively, compared with the existing second-order polynomial approximation. The code is available at https: //github. com/IDSL-SeoulTech/HyQ.

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YNIMG Journal 2023 Journal Article

Depth-wise profiles of iron and myelin in the cortex and white matter using χ-separation: A preliminary study

Subin Lee
Hyeong-Geol Shin
MinJun Kim
Jongho Lee

The in-vivo profiling of iron and myelin across cortical depths and underlying white matter has important implications for advancing knowledge about their roles in brain development and degeneration. Here, we utilize χ-separation, a recently-proposed advanced susceptibility mapping that creates positive ( χ p o s ) and negative ( χ n e g ) susceptibility maps, to generate the depth-wise profiles of χ p o s and χ n e g as surrogate biomarkers for iron and myelin, respectively. Two regional sulcal fundi of precentral and middle frontal areas are profiled and compared with findings from previous studies. The results show that the χ p o s profiles peak at superificial white matter (SWM), which is an area beneath cortical gray matter known to have the highest accumulation of iron within the cortex and white matter. On the other hand, the χ n e g profiles increase in SWM toward deeper white matter. These characteristics in the two profiles are in agreement with histological findings of iron and myelin. Furthermore, the χ n e g profiles report regional differences that agree with well-known distributions of myelin concentration. When the two profiles are compared with those of QSM and R2*, different shapes and peak locations are observed. This preliminary study offers an insight into one of the possible applications of χ-separation for exploring microstructural information of the human brain, as well as clinical applications in monitoring changes of iron and myelin in related diseases.

YNIMG Journal 2022 Journal Article

Sandwich spatial saturation for neuromelanin-sensitive MRI: Development and multi-center trial

Sooyeon Ji
Eun-Jung Choi
Beomseok Sohn
Kyoungwon Baik
Na-Young Shin
Won-Jin Moon
Seongbeom Park
Soohwa Song

Neuromelanin (NM)-sensitive MRI using a magnetization transfer (MT)-prepared T1-weighted sequence has been suggested as a tool to visualize NM contents in the brain. In this study, a new NM-sensitive imaging method, sandwichNM, is proposed by utilizing the incidental MT effects of spatial saturation RF pulses in order to generate consistent high-quality NM images using product sequences. The spatial saturation pulses are located both superior and inferior to the imaging volume, increasing MT weighting while avoiding asymmetric MT effects. When the parameters of the spatial saturation were optimized, sandwichNM reported a higher NM contrast ratio than those of conventional NM-sensitive imaging methods with matched parameters for comparability with sandwichNM (SandwichNM: 23.6 ± 5.4%; MT-prepared TSE: 20.6 ± 7.4%; MT-prepared GRE: 17.4 ± 6.0%). In a multi-vendor experiment, the sandwichNM images displayed higher means and lower standard deviations of the NM contrast ratio across subjects in all three vendors (SandwichNM vs. MT-prepared GRE; Vendor A: 28.4 ± 1.5% vs. 24.4 ± 2.8%; Vendor B: 27.2 ± 1.0% vs. 13.3 ± 1.3%; Vendor C: 27.3 ± 0.7% vs. 20.1 ± 0.9%). For each subject, the standard deviations of the NM contrast ratio across the vendors were substantially lower in SandwichNM (SandwichNM vs. MT-prepared GRE; subject 1: 1.5% vs. 8.1%, subject 2: 1.1 % vs. 5.1%, subject 3: 0.9% vs. 4.0%, subject 4: 1.1% vs. 5.3%), demonstrating consistent contrasts across the vendors. The proposed method utilizes product sequences, requiring no alteration of a sequence and, therefore, may have a wide practical utility in exploring the NM imaging.

YNIMG Journal 2021 Journal Article

DeepResp: Deep learning solution for respiration-induced B0 fluctuation artifacts in multi-slice GRE

Hongjun An
Hyeong-Geol Shin
Sooyeon Ji
Woojin Jung
Sehong Oh
Dongmyung Shin
Juhyung Park
Jongho Lee

Respiration-induced B0 fluctuation corrupts MRI images by inducing phase errors in k-space. A few approaches such as navigator have been proposed to correct for the artifacts at the expense of sequence modification. In this study, a new deep learning method, which is referred to as DeepResp, is proposed for reducing the respiration-artifacts in multi-slice gradient echo (GRE) images. DeepResp is designed to extract the respiration-induced phase errors from a complex image using deep neural networks. Then, the network-generated phase errors are applied to the k-space data, creating an artifact-corrected image. For network training, the computer-simulated images were generated using artifact-free images and respiration data. When evaluated, both simulated images and in-vivo images of two different breathing conditions (deep breathing and natural breathing) show improvements (simulation: normalized root-mean-square error (NRMSE) from 7. 8 ± 5. 2% to 1. 3 ± 0. 6%; structural similarity (SSIM) from 0. 88 ± 0. 08 to 0. 99 ± 0. 01; ghost-to-signal-ratio (GSR) from 7. 9 ± 7. 2% to 0. 6 ± 0. 6%; deep breathing: NRMSE from 13. 9 ± 4. 6% to 5. 8 ± 1. 4%; SSIM from 0. 86 ± 0. 03 to 0. 95 ± 0. 01; GSR 20. 2 ± 10. 2% to 5. 7 ± 2. 3%; natural breathing: NRMSE from 5. 2 ± 3. 3% to 4. 0 ± 2. 5%; SSIM from 0. 94 ± 0. 04 to 0. 97 ± 0. 02; GSR 5. 7 ± 5. 0% to 2. 8 ± 1. 1%). Our approach does not require any modification of the sequence or additional hardware, and may therefore find useful applications. Furthermore, the deep neural networks extract respiration-induced phase errors, which is more interpretable and reliable than results of end-to-end trained networks.

YNIMG Journal 2021 Journal Article

χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain

Hyeong-Geol Shin
Jingu Lee
Young Hyun Yun
Seong Ho Yoo
Jinhee Jang
Se-Hong Oh
Yoonho Nam
Sehoon Jung

Obtaining a histological fingerprint from the in-vivo brain has been a long-standing target of magnetic resonance imaging (MRI). In particular, non-invasive imaging of iron and myelin, which are involved in normal brain functions and are histopathological hallmarks in neurodegenerative diseases, has practical utilities in neuroscience and medicine. Here, we propose a biophysical model that describes the individual contribution of paramagnetic (e.g., iron) and diamagnetic (e.g., myelin) susceptibility sources to the frequency shift and transverse relaxation of MRI signals. Using this model, we develop a method, χ-separation, that generates the voxel-wise distributions of the two sources. The method is validated using computer simulation and phantom experiments, and applied to ex-vivo and in-vivo brains. The results delineate the well-known histological features of iron and myelin in the specimen, healthy volunteers, and multiple sclerosis patients. This new technology may serve as a practical tool for exploring the microstructural information of the brain.

YNIMG Journal 2020 Journal Article

Exploring linearity of deep neural network trained QSM: QSMnet+

Woojin Jung
Jaeyeon Yoon
Sooyeon Ji
Joon Yul Choi
Jae Myung Kim
Yoonho Nam
Eung Yeop Kim
Jongho Lee

Recently, deep neural network-powered quantitative susceptibility mapping (QSM), QSMnet, successfully performed ill-conditioned dipole inversion in QSM and generated high-quality susceptibility maps. In this paper, the network, which was trained by healthy volunteer data, is evaluated for hemorrhagic lesions that have substantially higher susceptibility than healthy tissues in order to test “linearity” of QSMnet for susceptibility. The results show that QSMnet underestimates susceptibility in hemorrhagic lesions, revealing degraded linearity of the network for the untrained susceptibility range. To overcome this limitation, a data augmentation method is proposed to generalize the network for a wider range of susceptibility. The newly trained network, which is referred to as QSMnet+, is assessed in computer-simulated lesions with an extended susceptibility range (−1. 4 ppm to +1. 4 ppm) and also in twelve hemorrhagic patients. The simulation results demonstrate improved linearity of QSMnet+ over QSMnet (root mean square error of QSMnet+: 0. 04 ppm vs. QSMnet: 0. 36 ppm). When applied to patient data, QSMnet+ maps show less noticeable artifacts to those of conventional QSM maps. Moreover, the susceptibility values of QSMnet+ in hemorrhagic lesions are better matched to those of the conventional QSM method than those of QSMnet when analyzed using linear regression (QSMnet+: slope = 1. 05, intercept = −0. 03, R2 = 0. 93; QSMnet: slope = 0. 68, intercept = 0. 06, R2 = 0. 86), consolidating improved linearity in QSMnet+. This study demonstrates the importance of the trained data range in deep neural network-powered parametric mapping and suggests the data augmentation approach for generalization of network. The new network can be applicable for a wide range of susceptibility quantification.

YNIMG Journal 2019 Journal Article

Advances in gradient echo myelin water imaging at 3T and 7T

Hyeong-Geol Shin
Se-Hong Oh
Masaki Fukunaga
Yoonho Nam
Doohee Lee
Woojin Jung
Minju Jo
Sooyeon Ji

Gradient echo myelin water imaging (GRE-MWI) is an MRI technique to measure myelin concentration and involves the analysis of signal decay characteristics of the multi-echo gradient echo data. The method provides a myelin water fraction as a quantitative biomarker for myelin. In this work, a new sequence and post-processing methods were proposed to generate high quality GRE-MWI images at 3T and 7T. In order to capture the rapidly decaying myelin water signals, a bipolar readout GRE sequence was designed with "gradient pairing, " compensating for the eddy current effects. The flip angle dependency from the multi-compartmental T1 effects was explored and avoided using a 2D multi-slice acquisition with a long TR. Additionally, the sequence was tested for the effects of inflow and magnetization transfer and demonstrated robustness to these error sources. Lastly, the temporal and spatial B0 inhomogeneity effects were mitigated by using the B0 navigator and field inhomogeneity corrections. Using the method, high-quality myelin water images were successfully generated for the in-vivo human brain at both field strengths. When the myelin water fraction at 3T and 7T were compared, they showed a good correlation (R2 ≥ 0. 88; p < 0. 001) with a larger myelin water fraction at 7T. The proposed method also opens the possibility of high resolution (isotropic 1. 5 mm resolution) myelin water mapping at 7T.

YNICL Journal 2019 Journal Article

Myelin water imaging of moderate to severe diffuse traumatic brain injury

Joon Yul Choi
Tessa Hart
John Whyte
Amanda R. Rabinowitz
Se-Hong Oh
Jongho Lee
Junghoon J. Kim

Traumatic axonal injury (TAI), a signature injury of traumatic brain injury (TBI), is increasingly known to involve myelin damage. The objective of this study was to demonstrate the clinical relevance of myelin water imaging (MWI) by first quantifying changes in myelin water after TAI and then correlating those changes with measures of injury severity and neurocognitive performance. Scanning was performed at 3 months post-injury in 22 adults with moderate to severe diffuse TBI and 30 demographically matched healthy controls using direct visualization of short transverse component (ViSTa) MWI. Fractional anisotropy (FA) and radial diffusivity (RD) were also obtained using diffusion tensor imaging. Duration of post-traumatic amnesia (PTA) and cognitive processing speed measured by the Processing Speed Index (PSI) from Wechsler Adult Intelligence Scale-IV, were assessed. A between-group comparison using Tract-Based Spatial Statistics revealed that there was a widespread reduction of apparent myelin water fraction (aMWF) in TBI, consistent with neuropathology involving TAI. The group difference map of aMWF yielded topography that was different from FA and RD. Importantly, aMWF demonstrated significant associations with PTA (r = -0.564, p = .006) and PSI (r = 0.452, p = .035). In conclusion, reduced myelin water, quantified by ViSTa MWI, is prevalent in moderate-to-severe diffuse TBI and could serve as a potential biomarker for injury severity and prediction of clinical outcomes.

YNIMG Journal 2018 Journal Article

Quantitative susceptibility mapping using deep neural network: QSMnet

Jaeyeon Yoon
Enhao Gong
Itthi Chatnuntawech
Berkin Bilgic
Jingu Lee
Woojin Jung
Jingyu Ko
Hosan Jung

Deep neural networks have demonstrated promising potential for the field of medical image reconstruction, successfully generating high quality images for CT, PET and MRI. In this work, an MRI reconstruction algorithm, which is referred to as quantitative susceptibility mapping (QSM), has been developed using a deep neural network in order to perform dipole deconvolution, which restores magnetic susceptibility source from an MRI field map. Previous approaches of QSM require multiple orientation data (e. g. Calculation of Susceptibility through Multiple Orientation Sampling or COSMOS) or regularization terms (e. g. Truncated K-space Division or TKD; Morphology Enabled Dipole Inversion or MEDI) to solve an ill-conditioned dipole deconvolution problem. Unfortunately, they either entail challenges in data acquisition (i. e. long scan time and multiple head orientations) or suffer from image artifacts. To overcome these shortcomings, a deep neural network, which is referred to as QSMnet, is constructed to generate a high quality susceptibility source map from single orientation data. The network has a modified U-net structure and is trained using COSMOS QSM maps, which are considered as gold standard. Five head orientation datasets from five subjects were employed for patch-wise network training after doubling the training data using a model-based data augmentation. Seven additional datasets of five head orientation images (i. e. total 35 images) were used for validation (one dataset) and test (six datasets). The QSMnet maps of the test dataset were compared with the maps from TKD and MEDI for their image quality and consistency with respect to multiple head orientations. Quantitative and qualitative image quality comparisons demonstrate that the QSMnet results have superior image quality to those of TKD or MEDI results and have comparable image quality to those of COSMOS. Additionally, QSMnet maps reveal substantially better consistency across the multiple head orientation data than those from TKD or MEDI. As a preliminary application, the network was further tested for three patients, one with microbleed, another with multiple sclerosis lesions, and the third with hemorrhage. The QSMnet maps showed similar lesion contrasts with those from MEDI, demonstrating potential for future applications.

YNIMG Journal 2018 Journal Article

Variable density magnetization transfer (vdMT) imaging for 7 T MR imaging

Se-Hong Oh
Wanyong Shin
Jongho Lee
Mark J. Lowe

As the use of ultra-high field (UHF; ≥7T) magnetic resonance (MR) imaging expands, there is an increasing need to establish high-resolution MR imaging protocols for patients with neurological disease. Magnetization transfer (MT) imaging has been used to provide information about changes in the magnitude of the restricted protons that are caused by tissue damages. Several studies have found that MTR has a good sensitivity to measure changes in myelin concentration within the brain. Because of the much higher specific absorption rate (SAR) of tissue and longer acquisition time required for UHF, however, in-vivo studies using conventional pulsed MT sequences at UHF have not been well utilized. In this study, we introduce a new MT data acquisition approach using a 7T MR system, variable density magnetization transfer (vdMT) imaging, which can be reasonably included in a routine patient scan protocol with a much shorter scan time and reduced discomfort to the patient. To reduce SAR and scan time while maintaining at least similar MTR image quality to that obtained with the conventional method, a higher density of MT RF pulses was applied in the center of k-space, and sparsely applied MT RF pulses were used in the outer part of k-space. The fraction of k-space receiving 100% MT RF density and TR were optimized based on in-vivo ROI analysis, and results were confirmed with high-resolution MTR map using a vdMT approach from healthy controls and patients with multiple sclerosis (MS). The experimental results confirmed that vdMT imaging can cover a whole brain volume in an acceptable scan time for routine patient scans while providing MTR image quality at least similar to that obtained with conventional MT imaging (correlation coefficient=0. 95 in an agar-gel phantom [MT offset frequency=1kH], 0. 90 in a postmortem MS brain, and 0. 85 in the 4 healthy volunteers). MS lesions were associated with signal reductions in the postmortem MS brains and in the patients with MS. In this study, we have described a new approach for acquiring high-resolution MTR map of the whole brain volume using 7T MR imaging. This vdMT method provides similar image quality to that obtained with the conventional method, and shortens the scan time by reducing SAR. These results suggest that vdMT approach is a method that could be used for UHF scans of patients with neurological disease.

YNIMG Journal 2018 Journal Article

Whole brain g-ratio mapping using myelin water imaging (MWI) and neurite orientation dispersion and density imaging (NODDI)

Woojin Jung
Jingu Lee
Hyeong-Geol Shin
Yoonho Nam
Hui Zhang
Se-Hong Oh
Jongho Lee

MR g-ratio, which measures the ratio of the aggregate volume of axons to that of fibers in a voxel, is a potential biomarker for white matter microstructures. In this study, a new approach for acquiring an in-vivo whole human brain g-ratio map is proposed. To estimate the g-ratio, myelin volume fraction and axonal volume fraction are acquired using multi-echo gradient echo myelin water imaging (GRE-MWI) and neurite orientation dispersion and density imaging (NODDI), respectively. In order to translate myelin water fraction measured in GRE-MWI into myelin volume fraction, a new scaling procedure is proposed and validated. This scaling approach utilizes geometric measures of myelin structure and, therefore, provides robustness over previous methods. The resulting g-ratio map reveals an expected range of g-ratios (0. 71–0. 85 in major fiber bundles) with a small inter-subject coefficient of variance (less than 2%). Additionally, a few fiber bundles (e. g. cortico-spinal tract and optic radiation) show different constituents of myelin volume fraction and axonal volume fraction, indicating potentials to utilize the measures for deciphering fiber tracking.

YNIMG Journal 2017 Journal Article

An R2* model of white matter for fiber orientation and myelin concentration

Jingu Lee
Hyeong-Geol Shin
Woojin Jung
Yoonho Nam
Se-Hong Oh
Jongho Lee

Myelin, which consists of lipid bilayers, is one of the major constituents of white matter in the brain and has been suggested as a primary source of magnetic susceptibility contrasts. In this study, a new R2* model that simultaneously explains the effects of fiber orientation and myelin concentration is proposed and tested. In addition, a new approach that produces R2* maps without the effects of myelin is suggested. Experimental results demonstrate that the model reveals a high goodness of fit for the R2* distribution of white matter compared to a model that explains either fiber orientation or myelin concentration. The proposed R2* map shows a relatively uniform spatial distribution of R2* compared to the uncorrected R2* map and the fiber orientation or myelin concentration corrected R2* map.

YNIMG Journal 2015 Journal Article

Improved estimation of myelin water fraction using complex model fitting

Yoonho Nam
Jongho Lee
Dosik Hwang
Dong-Hyun Kim

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.

YNIMG Journal 2015 Journal Article

Physiological noise compensation in gradient-echo myelin water imaging

Yoonho Nam
Dong-Hyun Kim
Jongho Lee

In MRI, physiological noise which originates from cardiac and respiratory functions can induce substantial errors in detecting small signals in the brain. In this work, we explored the effects of the physiological noise and their compensation methods in gradient-echo myelin water imaging (GRE-MWI). To reduce the cardiac function induced inflow noise, flow saturation RF pulses were applied to the inferior portion of the head, saturating inflow blood signals. For the respiratory function induced B0 fluctuation compensation, a navigator echo was acquired, and respiration induced phase errors were corrected during reconstruction. After the compensations, the resulting myelin water images show substantially improved image quality and reproducibility. These improvements confirm the importance and usefulness of the physiological noise compensations in GRE-MWI.

YNIMG Journal 2013 Journal Article

Direct visualization of short transverse relaxation time component (ViSTa)

Se-Hong Oh
Michel Bilello
Matthew Schindler
Clyde E. Markowitz
John A. Detre
Jongho Lee

White matter of the brain has been demonstrated to have multiple relaxation components. Among them, the short transverse relaxation time component (T2 <40ms; T2 ⁎ <25ms at 3T) has been suggested to originate from myelin water whereas long transverse relaxation time components have been associated with axonal and/or interstitial water. In myelin water imaging, T2 or T2 ⁎ signal decay is measured to estimate myelin water fraction based on T2 or T2 ⁎ differences among the water components. This method has been demonstrated to be sensitive to demyelination in the brain but suffers from low SNR and image artifacts originating from ill-conditioned multi-exponential fitting. In this study, a novel approach that selectively acquires short transverse relaxation time signal is proposed. The method utilizes a double inversion RF pair to suppress a range of long T1 signal. This suppression leaves short T2 ⁎ signal, which has been suggested to have short T1, as the primary source of the image. The experimental results confirm that after suppression of long T1 signals, the image is dominated by short T2 ⁎ in the range of myelin water, allowing us to directly visualize the short transverse relaxation time component in the brain. Compared to conventional myelin water imaging, this new method of direct visualization of short relaxation time component (ViSTa) provides high quality images. When applied to multiple sclerosis patients, chronic lesions show significantly reduced signal intensity in ViSTa images suggesting sensitivity to demyelination.

IROS Conference 2013 Conference Paper

Kernel-based tracking for improving sign detection performance

Jongho Lee
Young-Woo Seo
David Wettergreen

To be deployed in the real-world, automatic and semi-automatic systems should understand traffic rules by recognizing and comprehending contents of traffic signs, because traffic signs inform what driving behaviors should be. In this paper, we present the successful application of methods to improve the traffic sign localization performance. Given a potential sign region, our algorithm represents both the detected sign as a target and candidates in the subsequent frame as probability density functions. Then, our algorithm maximizes the similarity between a target and candidates to localize the sign. Finally, the maximum similarity among candidates is assigned as a tracked sign. The experimental results verify that our algorithm can robustly localize traffic signs in images under various weather conditions and driving scenarios.

YNIMG Journal 2013 Journal Article

Origin of B0 orientation dependent R2* (=1/T2*) in white matter

Se-Hong Oh
Young-Bo Kim
Zang-Hee Cho
Jongho Lee

Recent MRI studies have demonstrated that the relative orientation of white matter fibers to the B0 field significantly affects R2 ⁎ measurement. In this work, the origin of this effect was investigated by measuring R2 and R2 ⁎ in multiple orientations and fitting the results to magnetic susceptibility-based models and magic angle-based models. To further explore the source of magnetic susceptibility effect, the contribution of tissue iron to the orientation dependent R2 ⁎ contrast was investigated. Additionally, the effects of temperature on R2 ⁎ and orientation dependent R2 ⁎ contrasts were studied to understand the differences reported between a fixed specimen at room temperature and in vivo at body temperature. The results suggest that the B0 dependent R2 ⁎ variation is better explained by the magnetic susceptibility-based model with susceptibility anisotropy. However, extracting tissue iron did not reduce the orientation dependent R2 ⁎ contrast, suggesting iron is not the origin of the contrast. This leaves susceptibility effects from myelin as the most probable origin of the contrast. Temperature showed large contribution on both R2 ⁎ and orientation dependent R2 ⁎ contrasts, explaining a portion of the contrast difference between the in-vivo and in-vitro conditions.

YNIMG Journal 2012 Journal Article

The contribution of myelin to magnetic susceptibility-weighted contrasts in high-field MRI of the brain

Jongho Lee
Karin Shmueli
Byeong-Teck Kang
Bing Yao
Masaki Fukunaga
Peter van Gelderen
Sara Palumbo
Francesca Bosetti

T2*-weighted gradient-echo MRI images at high field (≥7T) have shown rich image contrast within and between brain regions. The source for these contrast variations has been primarily attributed to tissue magnetic susceptibility differences. In this study, the contribution of myelin to both T2* and frequency contrasts is investigated using a mouse model of demyelination based on a cuprizone diet. The demyelinated brains showed significantly increased T2* in white matter and a substantial reduction in gray-white matter frequency contrast, suggesting that myelin is a primary source for these contrasts. Comparison of in-vivo and in-vitro data showed that, although tissue T2* values were reduced by formalin fixation, gray-white matter frequency contrast was relatively unaffected and fixation had a negligible effect on cuprizone-induced changes in T2* and frequency contrasts.

YNIMG Journal 2011 Journal Article

Improving contrast to noise ratio of resonance frequency contrast images (phase images) using balanced steady-state free precession

Jongho Lee
Masaki Fukunaga
Jeff H. Duyn

Recent MRI studies have exploited subtle magnetic susceptibility differences between brain tissues to improve anatomical contrast and resolution. These susceptibility differences lead to resonance frequency shifts which can be visualized by reconstructing the signal phase in conventional gradient echo (GRE) acquisition techniques. In this work, a method is proposed to improve the contrast to noise ratio per unit time (CNR efficiency) of anatomical MRI based on resonance frequency contrast. The method, based on the balanced steady-state free precession (bSSFP) MRI acquisition technique, was evaluated in its ability to generate contrast between gray and white matter in human brain at 3T and 7T. The results show substantially improved CNR efficiency of bSSFP phase images (2. 85±0. 21 times at 3T and 1. 71±0. 11 times at 7T) compared to the GRE data in a limited spatial area. This limited spatial coverage is attributed to the sensitivity of bSSFP to macroscopic B0 inhomogeneities. With this CNR improvement, high resolution bSSFP phase images (resolution=0. 3×0. 3×2mm3, acquisition time=10min) acquired at 3T had sufficient CNR to allow the visualization of cortical laminar structures in in vivo human primary visual cortex. Practical application of the proposed method may require improvement of B0 homogeneity and stability by additional preparatory scans and/or compensation schemes such as respiration and drift compensation. Without these additions, the CNR benefits of the method may be limited to studies at low field or limited regions of interest.

YNIMG Journal 2011 Journal Article

T 2 *-based fiber orientation mapping

Jongho Lee
Peter van Gelderen
Li-Wei Kuo
Hellmut Merkle
Afonso C. Silva
Jeff H. Duyn

Recent MRI studies at high field have observed that, in certain white matter fiber bundles, the signal in T2 ⁎-weighted MRI (i. e. MRI sensitized to apparent transverse relaxivity) is dependent on fiber orientation θ relative to B0. In this study, the characteristics of this dependency are quantitatively investigated at 7T using ex-vivo brain specimens, which allowed a large range of rotation angles to be measured. The data confirm the previously suggested variation of R2 ⁎ (=1/T2*) with θ and also indicate that this dependency takes the shape of a combination of sin2θ and sin4θ functions, with modulation amplitudes (=ΔR2 ⁎) reaching 6. 44±0. 15Hz (or ΔT2 ⁎ =2. 91±0. 33ms) in the major fiber bundles of the corpus callosum. This particular dependency can be explained by a model of local, sub-voxel scale magnetic field changes resulting from magnetic susceptibility sources that are anisotropic. As an illustration of a potential use of the orientation dependence of R2 ⁎, the feasibility of generating fiber orientation maps from R2 ⁎ data is investigated.

YNIMG Journal 2010 Journal Article

On the contribution of deoxy-hemoglobin to MRI gray–white matter phase contrast at high field

Jongho Lee
Yoshiyuki Hirano
Masaki Fukunaga
Afonso C. Silva
Jeff H. Duyn

High field (≥7 T) MRI studies based on signal phase have been used to improve visualization of the fine structure of the brain, most notably the major white matter fiber bundles, the gray–white matter subdivision, and the laminar cortical architecture. The observed contrast has been attributed in part to local variations in magnetic susceptibility arising from iron in storage proteins and tissue lipid. Another contribution could come from the paramagnetic blood constituent deoxy-hemoglobin, the tissue concentration of which may vary through local variations in vascular density. To investigate this possibility, we examined phase contrast between gray and white matter in rats after intravenous administration of a superparamagnetic contrast agent at various dosages. At the maximum dosage (3 mg Fe/kg), which resulted in an estimated paramagnetic susceptibility shift 4–8 times larger than deoxy-hemoglobin, we observed a negligible increase in phase contrast between gray and white matter. This result suggests that endogenous deoxy-hemoglobin has no significant contribution to phase contrast between gray and white matter.