• Korean Journal of Digital Imaging in Medicine
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• v.13 no.1
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• pp.39-48
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• 2011

Uses a Tomographic scan image and Table Object Distance(TOD) price after measuring, uses accuracy and usability of blood vessel diameter(Vessel Diameter) measurement under comparison evaluating boil TOD Calibration. The patient who enforces Prosecuting Attorney abdomen Tomographic scan in the object the superior mesentery artery uses PACS View from abdomen fault image and from blood vessel diameter and the table measures the height until of the blood vessel. Uses Angio Catheter from Angiography(5 Fr.) and enforces is measured from PACS View the height until of the table which and the blood vessel at TOD Calibration price and the size of the superior mesentery artery inputs measures an superior mesentery artery building skill. Catheter Calibration input Agnio Catheter where uses in Angiography the size of the superior mesentery artery at Catheter Calibration price and they measure. Produced an accuracy from monitoring data and comparison evaluated. The statistical program used SPSS. TOD Calibration accuracy was 96.53%, standard deviation is 0.03829. Catheter Calibration accuracy of 92.91%, standard deviation is 0.05085. Represents a statistically significant difference(p = 0). According to age and gender was not statistically significant(p > 0.05). TOD Calibration correlation coefficient R-squared of 88.8%, Catheter Calibration of the R-squared is 75.5%. High accuracy of both methods. Through this study, CT images using the measured distance between the table and the Object, TOD Calibration accuracy higher than two Catheter Calibration was measured. TOD and Catheter Calibration represents a statistically significant difference(p = 0).

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.99-109
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• 2016

This paper presents a method for generating spatiotemporal images to detect the leukocyte motions in a microvessel. By using the constraint that the leukocytes move along the contour line of a blood vessel wall, the method detects leukocyte motions and then generates spatiotemporal images. the translational motion by a movement in vivo is removed first by the template matching method. Next, a blood vessel region is detected by the automatic threshold selection method to binarize the temporal variance image, then a blood vessel wall's contour is expressed by B-spline function. With the detected blood vessel wall's contour as an initial curve, the plasma layer of the best accurate position is determined to be the spatial axis by snake. Finally, the spatiotemporal images are generated. The experimental results show the spatiotemporal images are generated effectively through the comparison of each step of three image sequences.

• Journal of IKEEE
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• v.23 no.2
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• pp.557-570
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• 2019

In this study, a novel hierarchical approach is investigated to extract coronary vessel from X-ray angiogram. First, we propose to combine Decimation-free Directional Filter Bank (DDFB) and Homographic Filtering (HF) in order to enhance X-ray coronary angiographic image for segmentation purposes. Because the blood vessel ensures that blood flows in only one direction on vessel branch, the DDFB filter is suitable to be used to enhance the vessels at different orientations and radius. In the combination with HF filter, our method can simultaneously normalize the brightness across the image and increases contrast. Next, a coarse-to-fine strategy for iterative segmentation based on Otsu algorithm is applied to extract the main coronary vessels in different sizes. Furthermore, we also propose a new approach to segment very small vessels. Specifically, based on information of the main extracted vessels, we introduce a new method to extract junctions on the vascular tree and level of nodes on the tree. Then, the window based segmentation is applied to locate and extract the small vessels. Experimental results on our coronary X-ray angiography dataset demonstrate that the proposed approach can outperform standard method and attain the accuracy of 71.34%.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.422-427
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• 2014

This study provides a method to detect blood vessels shape using image processing techniques with the help of fluoroscopy equipments, providing high precision information about vessels' location and shape of inner path. It will assist for checking and monitoring the position of operating tools during vascular interventional treatment. The blood vessels shapes are gathered with X-ray images when a fluorescent medications are injected into patient's vessel and those images are processed for getting the boundaries of vessels. Then these data are merged with real-time CT-images. These image processing systems and procedures recognize the catheter, though continued computing algorithms are very useful for observer part on the automatic control system.

• Journal of IKEEE
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• v.26 no.1
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• pp.27-35
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• 2022

This paper proposes an ultrasound vessel-pattern imaging algorithm with low computational complexity. The proposed imaging algorithm reconstructs blood-vessel patterns by only detecting blood flow, and can be applied to a real-time signal processing hardware that extracts an ultrasonic finger-vessel pattern. Unlike a blood-flow imaging mode of typical ultrasound medical imaging device, the proposed imaging algorithm only reconstructs a presence of blood flow as an image. That is, since the proposed algorithm does not use an I/Q demodulation and detects a presence of blood flow by accumulating an absolute value of the clutter-filter output, a structure of the algorithm is relatively simple. To verify a complexity of the proposed algorithm, a simulation model for finger vessel was implemented using Field-II program. Through the behavioral simulation, it was confirmed that the processing time of the proposed algorithm is around 54 times less than that of the typical color-flow mode. Considering the required main building blocks and the amount of computation, the proposed algorithm is simple to implement in hardware such as an FPGA and an ASIC.

• Journal of KIISE:Software and Applications
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• v.29 no.3
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• pp.202-210
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• 2002

During the last few years, the extraction and reconstruction of the blood vessels in the medical image has been actively researched and the analysis for the retinal vessel structure has provided important information for diagnosis and remedy of the retinopathy patients. In this research, we propose the algorithm that tracks automatically the entire retinal vessel in retinal image acquired by the ICG(IndoCyanine Green) technology. This algorithm extracts contours and centers by estimating the local maxima and processing directions and detects bifurcations and junctions by comparing direction components of the local maxima from the gradient magnitude profile of each blood vessel. We present experimental results that the entire blood vessel is automatically reconstructed and is excellent in accuracy and connectivity after applying our algorithm to the ICG retinal images of patients.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.201-206
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• 2003

In clinical practice, CT Angiography is a powerful technique for the visualziation of blood flow in arterial vessels throughout the body. However CT Angiography images of blood vessels anywhere in the body may be fuzzy if the patient moves during the exam. In this paper, we propose a novel technique for removing global motion artifacts in the 3D space. The proposed methods are based on the two key ideas as follows. First, the method involves the extraction of a set of feature points by using a 3D edge detection technique based on image gradient of the mask volume where enhanced vessels cannot be expected to appear, Second, the corresponding set of feature points in the contrast volume are determined by correlation-based registration. The proposed method has been successfully applied to pre- and post-contrast CTA brain dataset. Since the registration for motion correction estimates correlation between feature points extracted from skull area in mask and contrast volume, it offers an accelerated technique to accurately visualize blood vessels of the brain.

• Journal of Physiology & Pathology in Korean Medicine
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• v.18 no.3
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• pp.789-791
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• 2004

We study on the video-capillaroscopy system for look a.t the nail fold capillary by the computer. This system is composed of the luminous source-producer, image-input, phase microscope. The method and contents of observation on this system are seperated from the image-analysis of nail fold capillary form-patterns and the currents of hematocytes. Therefore we think this system is possible to the practical clinic use for the basic model on the cardiac failure and the deficiency(血虛), stagnant(血瘀) of blood in human.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.397-398
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• 2019

망막혈관 영상에서(retinal image) 혈관의 모양 또는 생성변화를 효과적으로 검진하기 위해서 망막혈관을 자동적으로 분리하는 영상분할 기법의 개발은 매우 중요한 사안이다. 이를 위해서 주로 망막혈관영상의 잡음을 억제하고 또한 혈관의 명암대비도(contrast)를 증가시키는 전처리 과정을 거쳐서 혈관의 국부적인 화소값의 변화, 방향성을 판별하여 혈관을 자동적으로 검출하는 방법들이 제시되어왔으며 최근에는 합성곱 신경망(CNN) 딥러닝 학습모델을 활용한 망막혈관 분리 알고리즘들이 제시되고 있다.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.77-82
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• 2019

Diabetic retinopathy is a complicated form of diabetes due to circulatory disorder in the peripheral blood vessels of the retina. We segment the microvessel for diagnosing diabetic retinophathy. The conventional methods using filter and features can segment the thick blood vessels, but it has relatively weak for segmenting fine blood vessels. In pre-processing step, noise reduction filter and histogram equalization are applied to suppress the noise and enhance the image contrast. Then, deep learning technique is used for pixel-by-pixel segmentation. The accuracy of conventional methods is between 90% to 94%, while the proposed method has improved as 95% accuracy. There is a problem of segmentation error around the optic disc and exudate due to the network depth. However the accuracy can be improved by modifying the network architecture in the future.