• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.188-194
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• 2013

In this paper, we proposed a new method for pulmonary vessels image segmentation and refinement from pulmonary image. Proposed method consist of following five steps. First, threshold estimation is performed by polynomial regression analysis of histogram variation rate of the pulmonary image. Second, segmentation of pulmonary vessels object is performed by density-based segmentation method based on estimated threshold in first step. Third, 2D connected component labeling method is applied to segmented pulmonary vessels. The seed point of both side diaphragms is determined by eccentricity and size of component. Fourth step is diaphragm extraction by 3D region growing method at the determined seed point. Finally, noise cancelation of pulmonary vessels image is performed by 3D connected component labeling method. The experimental result is showed accurately pulmonary vessels image segmentation, the diaphragm extraction and the noise cancelation of the pulmonary vessels image.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1073-1081
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• 2009

In this paper, we proposed new method to enhance choroidal vessels by suppressing retina vessels brightness. It is well-known that CNV(choroidal neovascularization) is related with sight loss. The main feature of CNV is the occurrence of new vessels in choroid. Unfortunately, because retina vessels brightness is stronger than choroidal vessels brightness in ICGA(indocynanine green angiography) image, so that the choroidal vessels were hardly recognized. Therefore, for correct diagnosis, the choroidal vessels must be enhanced in ICGA image. The proposed enhancement method consists of 3 strategies. First, the retina vessels were detected by multi scale enhancement technique, hysteresis thresholding, KNN(Kth-nearest neighbor) classification method. And then, a retina vessel mask was generated from detection result. Next, the brightness of retina vessels was suppressed by the proposed conditional region erosion method and mask region until the mask region was vanished. Finally, the brightness of choroidal vessel was enhanced on processed image. Through an experiment, we had confirmed that the proposed method was robust and efficient.

• 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.

• 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.

• 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.

• 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.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 Internet Computing and Services
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• v.7 no.4
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• pp.33-43
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• 2006

This paper proposes a method to extract coronary arteries effectively in the angiography, In general. DSA(Digital Subtraction Angiography) is a well-established technique for the visualization of coronary arteries, DSA involves the subtraction of a mask image, an image of a heart before the injection of contrast medium, from a live image, However, this technique is sensitive to the movement of background and can cause wrong detection due to the variance of background intensity between two images. Therefore, this paper solves the structural problem resulted from background movement by selecting an image which has the least difference of movement through the similarity analysis of background texture, and it extracts only the blood vessels effectively through local intensity correction of the selected images, Experimental results show that the proposed method has the lower false-detection rate and higher accuracy rate than existing methods.

• Journal of Biomedical Engineering Research
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• v.29 no.5
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• pp.348-354
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• 2008

Segmenting vessels in lower extremity CT images is very difficult because of gray level variation, connection to bones, and their small sizes. Instead of segmenting vessels, we propose an approach that segments bones and subtracts them from the original CT images. The subtracted images can contain not only connected vessel structures but also isolated vessels, which are very difficult to detect using conventional vessel segmentation methods. The proposed method initially grows a 3-dimensional (3D) volume with a seeded region growing (SRG) using an adaptive threshold and then detects junctions and forked branches. The forked branches are classified into either bone branches or vessel branches based on appearance, shape, size change, and moving velocity of the branch. The final volume is re-grown by collecting connected bone branches. The algorithm has produced promising results for segmenting bone structures in several tens of vessel-enhanced CT image data sets of lower extremities.

• International Journal of Contents
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• v.2 no.3
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• pp.27-32
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• 2006

We present an effective algorithm for automatic tracing of retinal vessel structure and vascular landmark extraction of bifurcations and ending points. In this paper we deal with vascular patterns from RGB images for personal identification. Vessel tracing algorithms are of interest in a variety of biometric and medical application such as personal identification, biometrics, and ophthalmic disorders like vessel change detection. However eye surface vasculature tracing in RGB images has many problems which are subject to improper illumination, glare, fade-out, shadow and artifacts arising from reflection, refraction, and dispersion. The proposed algorithm on vascular tracing employs multi-stage processing of ten-layers as followings: Image Acquisition, Image Enhancement by gray scale retinal image enhancement, reducing background artifact and illuminations and removing interlacing minute characteristics of vessels, Vascular Structure Extraction by connecting broken vessels, extracting vascular structure using eight directional information, and extracting retinal vascular structure, and Vascular Landmark Extraction by extracting bifurcations and ending points. The results of automatic retinal vessel extraction using jive different thresholds applied 34 eye images are presented. The results of vasculature tracing algorithm shows that the suggested algorithm can obtain not only robust and accurate vessel tracing but also vascular landmarks according to thresholds.