• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.421-428
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• 2014

Like Alzheimer's disease, Parkinson's Disease(PD) is one of the most common neurodegenerative brain disorders. PD results from the deterioration of dopaminergic neurons in the brain region called the substantia nigra. Currently there is no cure for PD, but diagnosing in its early stage is important to provide treatments for relieving the symptoms and maintaining quality of life. Unlike many diagnosis methods of PD which use a single biomarker, we developed a diagnosis method that uses both biochemical biomarkers and imaging biomarkers. Our method uses ${\alpha}$-synuclein protein levels in the cerebrospinal fluid and diffusion tensor images(DTI). It achieved an accuracy over 91.3% in the 10-fold cross validation, and the best accuracy of 72% in an independent testing, which suggests a possibility for early detection of PD. We also analyzed the characteristics of the brain fiber pathways of Parkinson's disease patients and normal elderly people.

• Clinics in Shoulder and Elbow
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• v.25 no.1
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• pp.15-21
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• 2022

Background: This study was performed to identify the incidence of screw in-type lateral anchor pull-out in patients older than 60 years who underwent rotator cuff repair for large to massive rotator cuff tear (RCT). Methods: We reviewed 25 patients over 60 who were diagnosed with large to massive RCT and underwent arthroscopic rotator cuff repair in our hospital from March 2017 to February 2021. Preoperative tear size (anterior to posterior, medial to lateral) was measured via preoperative magnetic resonance imaging (MRI). All 25 patients underwent MRI scanning on postoperative day 1 and at 3 months after surgery. The change of anchor position was measured in axial views on MRI images postoperative day 1 and 3 months after surgery. And it was statistically compared according to bone mineral density (BMD), sex, and number of lateral anchors. Results: Two MRIs (postoperative day 1 and 3 months) in 25 patients were compared. Anchor pull-out occurred in six patients during 3 months (6.7%), and the mean pull-out length difference was 1.56 mm (range, 0.16-2.58 mm). There was no significant difference in the number of pull-out anchors, degree of pull-out difference by comparing BMD (A, BMD≤-2.5; B, BMD>-2.5), sex, or number of anchors used in each surgery (C, two anchors; D, three anchors) (p>0.05). Conclusions: Pull-out of screw in-type anchors was rarely observed and the mean pull-out length difference was negligibly small in our study. The screw in-type lateral anchor seems to be a decent option without concern of anchor pull-out even in elderly patients.

• Journal of the Korean Society of Radiology
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• v.84 no.5
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• pp.1140-1145
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• 2023

Cerebral amyloid angiopathy-related inflammation (CAA-RI) is an encephalopathy caused by inflammation of β-amyloid peptide deposition in cerebrovascular vessels. It is a rare disease that mainly occurs in the elderly and is characterized by rapidly progressive dementia, headache, seizures, and focal neurologic deficits. CAA-RI can demonstrate characteristic brain MRI findings and can be reversed by steroids or other immunosuppressive therapies. Here, we report a case of CAA-RI, which was initially misdiagnosed as a subacute infarction but was diagnosed while reviewing follow-up brain MRI images, and spontaneous remission was achieved.

• Journal of Broadcast Engineering
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• v.28 no.2
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• pp.238-241
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• 2023

Recently deep learning models are widely used for various tasks such as facial recognition and face editing. Their training process often involves a dataset with imbalanced age distribution. It is because some age groups (teenagers and middle age) are more socially active and tends to have more data compared to the less socially active age groups (children and elderly). This imbalanced age distribution may negatively impact the deep learning training process or the model performance when tested against those age groups with less data. To this end, we propose an age-controllable face synthesis technique using a feature decomposition to classify age from facial images which can be utilized to synthesize novel data to balance out the age distribution. We perform extensive qualitative and quantitative evaluation on our proposed technique using the FFHQ dataset and we show that our method has better performance than existing method.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.146-151
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• 2019

In this paper, we developed a multi-view video content based on real-world technology and a pilot using the production technology, and provided realistic contents production technology that can select a desired direction at a user 's view point by providing users with various viewpoint images. We also created multi-view video contents that can indirectly experience local cultural tourism resources and produced cyber tour contents based on multi-view video (realistic technology). This technology development can be used to create 3D interactive real-world contents that are used in all public education fields such as libraries, kindergartens, elementary schools, middle schools, elderly universities, housewives classrooms, lifelong education centers, The domestic VR market is still in it's infancy, and it's expected to develop in combination with the 3D market related to games and shopping malls. As the domestic educational trend and the demand for social public education system are growing, it is expected to increase gradually.

• Investigative Magnetic Resonance Imaging
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• v.17 no.4
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• pp.275-285
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• 2013

Purpose : The objective of this study was to investigate effects of different smoothing kernel sizes on brain tissue-masked susceptibility-weighted images (SWI) obtained from normal elderly subjects using voxel-based analyses. Materials and Methods: Twenty healthy human volunteers (mean $age{\pm}SD$ = $67.8{\pm}6.09$ years, 14 females and 6 males) were studied after informed consent. A fully first-order flow-compensated three-dimensional (3D) gradient-echo sequence ran to obtain axial magnitude and phase images to generate SWI data. In addition, sagittal 3D T1-weighted images were acquired with the magnetization-prepared rapid acquisition of gradient-echo sequence for brain tissue segmentation and imaging registration. Both paramagnetically (PSWI) and diamagnetically (NSWI) phase-masked SWI data were obtained with masking out non-brain tissues. Finally, both tissue-masked PSWI and NSWI data were smoothed using different smoothing kernel sizes that were isotropic 0, 2, 4, and 8 mm Gaussian kernels. The voxel-based comparisons were performed using a paired t-test between PSWI and NSWI for each smoothing kernel size. Results: The significance of comparisons increased with increasing smoothing kernel sizes. Signals from NSWI were greater than those from PSWI. The smoothing kernel size of four was optimal to use voxel-based comparisons. The bilaterally different areas were found on multiple brain regions. Conclusion: The paramagnetic (positive) phase mask led to reduce signals from high susceptibility areas. To minimize partial volume effects and contributions of large vessels, the voxel-based analysis on SWI with masked non-brain components should be utilized.

• Korea Science and Art Forum
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• v.31
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• pp.171-180
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• 2017

The purpose of this study is to analyze the characteristics of color image for establishing the color environment contributing to the promotion of public health in the public health facilities and to utilize it as data of public health color plan and index development. For this purpose, the results of the previous precedent studies were integrated and public health facilities were classified into medical facilities (general hospitals), health facilities (public health centers), and sub - healing facilities (elderly care facilities). We visited 18 public health facilities in total, measured the environmental color of with a spectroscopic, compared the results and the precedent studies results, and identified color image characteristics and future supplement points. The results are as follows. First, the previous studies related to the environment color image vocabulary of the public health facilities, it prefer comfortable, bright and positive image. Second, as a result of direct measurement the environmental color of the public health facilities, it is found that most of them use the high brightness and low saturation color of Y series. Third, as a result of analyzing vocabulary of environmental color image of public health facilities, 'natural' image showed the highest frequency, and other images such as 'gentle' and 'decent' appeared. It was difficult to understand the characteristics of the color image vocabularies of public health facilities. This study is a convergence study of color science and environmental design, and it extends the scope of multidisciplinary research related to design and it will be helpful in environmental planning on user's emotion.

• Investigative Magnetic Resonance Imaging
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• v.25 no.3
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• pp.164-171
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• 2021

Purpose: Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD). Brain atrophy in this disease spectrum begins in the medial temporal lobe structure, which can be recognized by magnetic resonance imaging. To overcome the unsatisfactory inter-observer reliability of visual evaluation, quantitative brain volumetry has been developed and widely investigated for the diagnosis of MCI and AD. The aim of this study was to assess the prediction accuracy of quantitative brain volumetry using a fully automated segmentation software package, NeuroQuant^®, for the diagnosis of MCI. Materials and Methods: A total of 418 subjects from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease cohort were included in our study. Each participant was allocated to either a cognitively normal old group (n = 285) or an MCI group (n = 133). Brain volumetric data were obtained from T1-weighted images using the NeuroQuant software package. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to investigate relevant brain regions and their prediction accuracies. Results: Multivariate logistic regression analysis revealed that normative percentiles of the hippocampus (P < 0.001), amygdala (P = 0.003), frontal lobe (P = 0.049), medial parietal lobe (P = 0.023), and third ventricle (P = 0.012) were independent predictive factors for MCI. In ROC analysis, normative percentiles of the hippocampus and amygdala showed fair accuracies in the diagnosis of MCI (area under the curve: 0.739 and 0.727, respectively). Conclusion: Normative percentiles of the hippocampus and amygdala provided by the fully automated segmentation software could be used for screening MCI with a reasonable post-processing time. This information might help us interpret structural MRI in patients with cognitive impairment.

• The Journal of Korean Medicine
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• v.29 no.1
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• pp.192-199
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• 2008

Objective : Silent infarct is more common in healthy elderly people and seems associated with risk of future stroke. However, the prevalence and risk factors of silent infarct are unclear. We investigated the prevalence and risk factors of silent infarct. Methods : 56 first-ever cerebral infarct patients were enrolled in this study. CT images were made of all 56 patients. We divided them into two groups according to the presence of silent infarcts and comparedage, sex, education period, WHR, hypertension, diabetes mellitus, hyperlipidemia, smoking, numbness and weakness of thumb and index finger, neck stiffness, facial spasm, and blepherospasm. Result : Silent infarcts were found in 24 patients(43%). Most infarcts(48%) were located in basal ganglia. Age, sex, education period, WHR, numbness and weakness of thumb and index finger, neck stiffness, facial spasm, and blepherospasm were similar between the two groups. Diabetes mellitus, hyperlipidemia, and smoking were higher in the silent infarct group. Hypertension was higher in the non-silent infarct group. Conclusion : The prevalence of silent infarct in first-ever cerebral infarction patients was 43% and diabetes mellitus, hyperlipidemia, and smoking were higher in silent infarct patients.

• Korean Journal of Biological Psychiatry
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• v.21 no.3
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• pp.81-86
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• 2014

Objectives Total intracranial volume (TIV) is a major nuisance of neuroimaging research for interindividual differences of brain structure and function. Authors intended to prove the reliability of the atlas scaling factor (ASF) method for TIV estimation in FreeSurfer by comparing it with the results of manual tracing as reference method. Methods The TIVs of 26 normal children and 26 children with attention-deficit hyperactivity disorder (ADHD) were obtained by using FreeSurfer reconstruction and manual tracing with T1-weighted images. Manual tracing performed in every 10th slice of MRI dataset from midline of sagittal plane by one researcher who was blinded from clinical data. Another reseacher performed manual tracing independently for randomly selected 20 dataset to verify interrater reliability. Results The interrater reliability was excellent (intraclass coefficient = 0.91, p < 7.1e-07). There were no significant differences of age and gender distribution between normal and ADHD groups. No significant differences were found between TIVs from ASF method and manual tracing. Strong correlation between TIVs from 2 different methods were shown (r = 0.90, p < 2.2e-16). Conclusions The ASF method for TIV estimation by using FreeSurfer showed good agreement with the reference method. We can use the TIV from ASF method for correction in analysis of structural and functional neuroimaging studies with not only elderly subjects but also children, even with ADHD.