• Progress in Medical Physics
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• v.10 no.3
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• pp.159-168
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• 1999

Cardiac disease is one of the leading causes of death in Korea. In quantitative analysis of cardiac function and morphological information by three-dimensional reconstruction of magnetic resonance images, left ventricle provides an important role functionally and physiologically. However, existing procedures mostly rely on the extensive human interaction and are seldom evaluated on clinical applications. In this study, we developed a system which could perform automatic extraction of enpicardial and endocardial contour and analysis of cardiac function to evaluate reliability and stability of each system comparing with the result of ARGUS system offered 1.5T Siemens MRI system and manual method performed by clinicians. For various aspects, we investigated reliability of each system by compared with left ventricular contour, end-diastolic volume (EDV), end-systolic volume (ESV), stock volume (SV), ejection fraction (EF), cardiac output (CO) and wall thickness (WT). When comparing with manual method, extracted results of developed process using minimum error threshold (MET) method that automatically extracts contour from cardiac MR images and ARGUS system were demonstrated as successful rate 90% of the contour extraction. When calculating cardiac function parameters using MET and comparing with using correlation coefficients analysis method, the process extracts endocardial and epicardial contour using MET, values from automatic and ARGUS method agreed with manual values within :t 3% average error. It was successfully demonstrated that automatic method using threshold technique could provide high potential for assessing of each parameters with relatively high reliability compared with manual method. In this study, the method developed in this study could reduce processing time compared with ARGUS and manual method due to a simple threshold technique. This method is useful for diagnosis of cardiac disease, simulating physiological function and amount of blood flow of left ventricle. In addition, this method could be valuable in developing automatic systems in order to apply to other deformable image models.

• Investigative Magnetic Resonance Imaging
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• v.14 no.2
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• pp.115-120
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• 2010

Purpose : To separate and evaluate the low frequency spontaneous fluctuation BOLD signals from the functional magnetic resonance imaging data using sensorimotor active task. Materials and Methods : Twenty female archery players and twenty three control subjects were included in this study. Finger-tapping task consisted of three cycles of right finger tapping, with a subsequent 30 second rest. Blood oxygenation level-dependent (BOLD) data were collected using $T2^*$-weighted echo planar imaging at a 3.0 T scanner. A 3-D FSPGR T1-weighted images were used for structural reference. Image processing and statistical analyses were performed using SPM5 for active finger-tapping task and GIFT program was used for statistical analyses of low frequency spontaneous fluctuation BOLD signal. Results : Both groups showed the activation in the left primary motor cortex and supplemental motor area and in the right cerebellum for right finger-tapping task. ICA analysis using GIFT revealed independent components corresponding to contralateral and ipsilateral sensorimotor network and cognitive-related neural network. Conclusion : The current study demonstrated that the low frequency spontaneous fluctuation BOLD signals can be separated from the fMRI data using finger tapping paradigm. Also, it was found that these independent components correspond to spontaneous and coherent neural activity in the primary sensorimotor network and in the motor-cognitive network.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Journal of the Korean Society of Radiology
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• v.3 no.2
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• pp.27-31
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• 2009

Now a days, the Medical X-ray equipments has become digitalized from analog type such as film, cassette to CR, DR. And many scientists are still researching and developing the Medical X-ray equipment. In this study, we used the Bismuth tri-iodide to conversion material for digital X-ray equipments and we couldn't get the satisfying result than previous study, but it opened new possibility to cover the disadvantage of a-Se is high voltage aplly and difficultness of make. In this paper, we use $BiI_3$ powder(99.99%) as x-ray conversion material and make films that have thickness of 200um and the film size is $3cm{\times}3cm$. Also, we deposited an ITO(Indium Tin Oxide) electrode as top electrode and bottom electrode using a Magnetron Sputtering System. To evaluate a characteristics of the produced films, an electrical and structural properties are performed. Through a SEM analysis, we confirmed a surface and component part. And to analyze the electrical properties, darkcurrent, sensitivity and SNR(Signal to Noise Ratio) are measured. Darkcurrent is $1.6nA/cm^2$ and sensitivity is $0.629nC/cm^2$ and this study shows that the electrical properties of x-ray conversion material that made by screen printing method are similar to PVD method or better than that. This results suggest that $BiI_3$ is suitable for a replacement of a-Se because of the reduced manufacture processing and improved yield.

• Progress in Medical Physics
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• v.23 no.1
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• pp.62-69
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• 2012

The dose re-calculation process using Megavoltage cone-beam CT images is inevitable process to perform the Adaptive Radiation Therapy (ART). The purpose of this study is to improve dose re-calculation accuracy using MVCBCT images by applying intensity calibration method and three dimensional rigid body transform and filtering process. The three dimensional rigid body transform and Gaussian smoothing filtering process to MVCBCT Rando phantom images was applied to reduce image orientation error and the noise of the MVCBCT images. Then, to obtain the predefined modification level for intensity calibration, the cheese phantom images from kilo-voltage CT (kV CT), MVCBCT was acquired. From these cheese phantom images, the calibration table for MVCBCT images was defined from the relationship between Hounsfield Units (HUs) of kV CT and MVCBCT images at the same electron density plugs. The intensity of MVCBCT images from Rando phantom was calibrated using the predefined modification level as discussed above to have the intensity of the kV CT images to make the two images have the same intensity range as if they were obtained from the same modality. Finally, the dose calculation using kV CT, MVCBCT with/without intensity calibration was applied using radiation treatment planning system. As a result, the percentage difference of dose distributions between dose calculation based on kVCT and MVCBCT with intensity calibration was reduced comparing to the percentage difference of dose distribution between dose calculation based on kVCT and MVCBCT without intensity calibration. For head and neck, lung images, the percentage difference between kV CT and non-calibrated MVCBCT images was 1.08%, 2.44%, respectively. In summary, our method has quantitatively improved the accuracy of dose calculation and could be a useful solution to enhance the dose calculation accuracy using MVCBCT images.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.123-126
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• 2012

This paper proposed a method to separate a liver into left and right liver lobes for simple and exact volumetry of the river graft at abdominal MDCT(Multi-Detector Computed Tomography) image before the living donor liver transplantation. A medical team can evaluate an accurate river graft with minimized interaction between the team and a system using this algorithm for ensuring donor's and recipient's safe. On the image of segmented liver, 2 points(PMHV: a point in Middle Hepatic Vein and PPV: a point at the beginning of right branch of Portal Vein) are selected to separate a liver into left and right liver lobes. Middle hepatic vein is automatically segmented using PMHV, and the cutting line is decided on the basis of segmented Middle Hepatic Vein. A liver is separated on connecting the cutting line and PPV. The volume and ratio of the river graft are estimated. The volume estimated using 2 points are compared with a manual volume that diagnostic radiologist processed and estimated and the weight measured during surgery to support proof of exact volume. The mean ${\pm}$ standard deviation of the differences between the actual weights and the estimated volumes was $162.38cm^3{\pm}124.39$ in the case of manual segmentation and $107.69cm^3{\pm}97.24$ in the case of 2 points method. The correlation coefficient between the actual weight and the manually estimated volume is 0.79, and the correlation coefficient between the actual weight and the volume estimated using 2 points is 0.87. After selection the 2 points, the time involved in separation a liver into left and right river lobe and volumetry of them is measured for confirmation that the algorithm can be used on real time during surgery. The mean ${\pm}$ standard deviation of the process time is $57.28sec{\pm}32.81$ per 1 data set ($149.17pages{\pm}55.92$).

• Cartoon and Animation Studies
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• s.14
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• pp.165-176
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• 2008

In the future there would be many kinds of digital images for many industrial markets. 3D stereoscopic images for variable fields; medical operation, film and animation, broadcasting, internet, game, or design for art and architecture. And many people to work about computer programming, and digital image making will concern about it more and more. However, these kinds works and studies are focused on the professional technical fields like 3D display or computer programming technology so far. To revitalize the market of a variable stereoscopic contents, there should build up the foundation for easy processing of the making stereoscopic images. This paper is based on stereoscopic making skills for anaglyph system. An anaglyph system has an old history about making stereoscopic images, and very simple method to produce the stereoscopic images. Particularly this study is focused on color compositing technique, and camera positioning on the compositing system. It will help optimization of the environments to create 3D motion graphic and animation contents.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.10
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• pp.530-540
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• 2005

Virtual colonoscopy is an easy and fast method to reconstruct the shape of colon and diagnose tumors inside the colon based on computed tomography images. This is a non-invasive method, which resolves weak points of previous invasive methods. The path for virtual colonoscopy should be generated rapidly and accurately for clinical examination. However, previous methods are computationally expensive because the data structure such as distance map should be constructed in the preprocessing and positions of all the points of the path needs to be calculated. In this paper, we propose the automatic path generation method based on visibility to decrease path generation time. The proposed method does not require preprocessing and generates small number of control points representing the Path instead of all points to generate the path rapidly. Also, our method generates the path based on visibility so that a virtual camera moves smoothly and a comfortable and accurate path is calculated for virtual navigation. Also, our method can be used for general virtual navigation of various kinds of pipes.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.295-306
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• 2016

The purpose of this paper is both to analyze research trends and to predict industrial flows using the meta-data from the previous studies on data quality. There have been many attempts to analyze the research trends in various fields till lately. However, analysis of previous studies on data quality has produced poor results because of its vast scope and data. Therefore, in this paper, we used a text mining, social network analysis for time series network analysis to analyze the vast scope and data of data quality collected from a Web of Science index database of papers published in the international data quality-field journals for 10 years. The analysis results are as follows: Decreases in Mathematical & Computational Biology, Chemistry, Health Care Sciences & Services, Biochemistry & Molecular Biology, Biochemistry & Molecular Biology, and Medical Information Science. Increases, on the contrary, in Environmental Sciences, Water Resources, Geology, and Instruments & Instrumentation. In addition, the social network analysis results show that the subjects which have the high centrality are analysis, algorithm, and network, and also, image, model, sensor, and optimization are increasing subjects in the data quality field. Furthermore, the industrial connection analysis result on data quality shows that there is high correlation between technique, industry, health, infrastructure, and customer service. And it predicted that the Environmental Sciences, Biotechnology, and Health Industry will be continuously developed. This paper will be useful for people, not only who are in the data quality industry field, but also the researchers who analyze research patterns and find out the industry connection on data quality.

• Korean Journal of Biological Psychiatry
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• v.26 no.1
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• pp.22-31
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• 2019

Objectives Previous studies have revealed inconsistent results on amygdala volume in adult bipolar disorder (BD) patients compared to healthy controls (HC). Since the amygdala encompasses multiple subregions, the subtle volume changes in each amygdala nucleus might have not been fully reflected in the measure of the total amygdala volume, causing discrepant results. Thus, we aimed to investigate volume changes in each amygdala subregion and their association with subtypes of BD, lithium use and clinical status of BD. Methods Fifty-five BD patients and 55 HC underwent T1-weighted structural magnetic resonance imaging. We analyzed volumes of the whole amygdala and each amygdala subregion, including the anterior amygdaloid area, cortico-amygdaloid transition area, basal, lateral, accessory basal, central, cortical, medial and paralaminar nuclei using the atlas in the FreeSurfer. The volume difference was analyzed using a one-way analysis of covariance with individual volumes as dependent variables, and age, sex, and total intracranial volume as covariates. Results The volumes of whole right amygdala and subregions including basal nucleus, accessory basal nucleus, anterior amygdaloid area, and cortico-amygdaloid transition area in the right amygdala of BD patients were significantly smaller for the HC group. No significant volume difference between bipolar I disorder and bipolar II disorder was found after the Bonferroni correction. The trend of larger volume in medial nucleus with lithium treatment was not significant after the Bonferroni correction. No significant correlation between illness duration and amygdala volume, and insignificant negative correlation were found between right central nucleus volume and depression severity. Conclusions Significant volume decrements of the whole amygdala, basal nucleus, accessory basal nucleus, anterior amygdaloid area, and cortico-amygdaloid transition area were found in the right hemisphere in adult BD patients, compared to HC group. We postulate that such volume changes are associated with altered functional activity and connectivity of amygdala nuclei in BD.