• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.11a
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• pp.1-2
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• 2011

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.119-128
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• 2014

The appearance of retinal blood vessels is an important diagnostic indicator of serious disease, such as hypertension, diabetes, cardiovascular disease, and stroke. Automatic segmentation of the retinal vasculature is a primary step towards automatic assessment of the retinal blood vessel features. This paper presents an automated method for the enhancement and segmentation of blood vessels in fundus images. To decrease the influence of the optic disk, and emphasize the vessels for each retinal image, a multidirectional morphological top-hat transform with rotating structuring elements is first applied to the background homogenized retinal image. Then, an improved multiscale line detector is presented to produce a vessel response image, and yield the retinal blood vessel tree for each retinal image. Since different line detectors at varying scales have different line responses in the multiscale detector, the line detectors with longer length produce more vessel responses than the ones with shorter length; the improved multiscale detector combines all the responses at different scales by setting different weights for each scale. The methodology is evaluated on two publicly available databases, DRIVE and STARE. Experimental results demonstrate an excellent performance that approximates the average accuracy of a human observer. Moreover, the method is simple, fast, and robust to noise, so it is suitable for being integrated into a computer-assisted diagnostic system for ophthalmic disorders.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.880-890
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• 2010

The intrasvascular ultrasound (IVUS) imaging technique is used to diagnose cerebrovascular diseases such as stroke. Recently, elasticity imaging methods have been investigated to diagnose blood clots attached to blood vessel intima. However, the IVUS imaging technique is an invasive method that requires a transducer to be inserted into blood vessel. In this paper, strain images are obtained of blood clots attached to blood vessel intima with data acquired from outside the blood vessel using a linear array transducer. In order to measure the displacement of blood vessel accurately, experimental data are acquired by steering ultrasound beams so that they can intersect the blood vessel wall at right angles. The acquired rf data are demodulated to the baseband. The resulting complex baseband signals are then processed by an autocorrelation algorithm to compute the blood vessel movement and thereby produce strain image. This proposed method is verified by experiments on a plastic blood vessel mimicking phantom. The efficacy of the proposed method was verified using a home-made blood vessel mimicking phantom. The blood vessel mimicking phantom was constructed by making a 6 mm diameter hollow cylinder inside it to simulate a blood vessel and adhering 2 mm thick soft plaque to the inner wall of the hollow cylinder. The RF data were acquired using a clinical ultrasound scanner (Accuvix XQ, Medison, Seoul. Korea) with a 7.5 MHz linear array transducer by steering ultrasound beams in steps of $1^{\circ}$ from $-40^{\circ}$ to $40^{\circ}$ for a total of 81 angles. Experimental results show that the plaque region near the blood vessel wall is softer than background tissue. Although the imaging region is restricted due to the limited range of angles for which scan lines are perpendicular to the wall, the feasibility of strain imaging is demonstrated.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.101-106
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• 2004

In this paper, a blood vessel in an angiographic image, which plays an importance role in the diagnose diseases including in the eyes, brain and heart, is enhanced by using a directed diffusion technique. A fundamental component of the angiographic analysis is vessel segmentation that the proposed method provides a preprocessing of the image into a form suitable for human analysis, or more importantly, for machine analysis such the segmentation. Vessel enhancement is a challenging problem due to the complex nature of vascular trees and to imaging imperfections. Some parts of the inherent imperfections in angiography are the intensity inhomogeneity between the larger and smaller vessels, and another imperfection is the leakage of contrast agent into the background tissue that provides to low contrast between vessels and tissue. In the proposed scheme, the directed diffusion solves the problem by formulating a local geometric structure, which consists of direction and scale of the blood vessels. The diffusion process uses the local structure to enhance by a diffusivity tensor. The proposed algorithm can be applied to maintain sharpness and coherence-smooth the intra-regions into homogeneity better than traditional diffusion methods, which are Gaussian regulation and coherence enhancing diffusion.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.155-156
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• 2009

In this paper we present 3D image analysis of liver and blood vessels using MDCT. The purpose is to enhance the performance of clinician in assessing anatomical information of liver and blood vessels. The system consists of two parts: 3D image reconstruction and analysis of the 3D liver and blood vessel image. The central vein of the liver is the most important blood vessel for the liver transplantation. We will find the central vein's location and characteristic, and will scheme out a computer assistant liver transplantation planning. It will be an effective tool for interventional radiology, surgical planning, and quantitative diagnosis.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.414-417
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• 1997

This paper presents vessel contour for extracting features and segmentating narrow blood vessels down to a diameter of two pixels in digital subtraction angiographic image. We present a new tracking algorithm for contour, mainly blood vessels in DSA image, and extracting properties such as their intensities, diameters, and center lines by exploiting spatial continuity. The proposed algorithm comes to detect blood vessel's boundary using difference edge detector one of homogeneity operator and find a next centerline position by direction vector of edge information. This algorithm enhanced variation of vessel's diameter compared to Sun's tracking algorithm and lessoned to compute as direction vector decide adaptively entire vessel's direction field. The processed images are intended to support radiologists in diagnosis, radiation therapy planning, and surgical planning. The algorithm should be useful for automating angiographic analyses of blood vessels.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.128-134
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• 2014

In this paper, we propose a detection method of the leukocyte motions in a microvessel by using spatiotemporal image analysis. The leukocyte motions that adhere to blood vessel walls can be visualized to move along the blood vessel wall's contours in a sequence of images. In this proposal method, we use the constraint that the leukocytes move along the blood vessel wall's contours and detect the leukocyte motions by using the spatiotemporal image analysis method. The generated spatiotemporal image is processed by a special-purpose orientation-selective filter and then subsequent grouping processes are done. The subsequent grouping processes select and group the leukocyte trace segments among all the segments obtained by simple thresholding and skeletonizing operations. Experimental results show that the proposed method can stably detect the leukocyte motions even when multiple leukocyte traces intersect each other.

• Applied Microscopy
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• v.47 no.2
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• pp.75-76
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• 2017

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.76-84
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• 2017

This paper presents an efficient method for generating spatiotemporal images in order to detect leukocyte motion in microvessels. Leveraging the constraint that leukocytes move along the contour line of the blood vessel wall, our proposed method efficiently generates spatiotemporal images for leukocyte motion detection. To that end, translational motion caused by in vivo movement is first removed by a template matching method. Second, the blood vessel region is detected by an automatic threshold selection method in order to binarize temporal variance images. Then, the contour of the blood vessel wall is expressed via B-spline function. Finally, using the detected blood vessel wall's contour as an initial curve, the plasma layer for the most accurate position is determined in order to find the spatial axis via snake, and the spatiotemporal images are generated. Experimental results show that the spatiotemporal images are generated effectively through comparison of each step with three images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.585-590
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• 2012

Coronary Intervention treatment has become the core that is the test of cardiac catheterization to conduct treatment with Coronary Arteriography. Operators must be careful in Coronary Intervention treatment because the stent is inserted into the point of narrowing of blood vessel. So, the operator must correctly recognize the path of blood vessel to deal with the problems which are damages and ruptures of blood vessel, and there would be some errors of finding the path of blood vessel by bad qualify of the image. Therefore in this paper, median filtering is conducted by preprocessing to evaluate the performance of the effect of noise of the image that affects quality of the image and Fuzzy Edge Extraction Techniques is tested by using Soble Edge Extraction Techniques to compare the performance with The Fuzzy Edge Extraction Techniques. In result, the performance, removing the noise and extracting the signal of Fuzzy Edge Extraction Techniques using median filtering, demonstrates the superiority.