• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.289-300
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• 1995

The conventionally used method requires centerline of vessels to estimate the vessel diameter. Two methods of estimating the centerline of vessels are reported : One is manually observer-defined method. This potentially contributes to inter-and intra-observer variability. And the other is to auto- matically detect the centerline of vessels. But this is very complicated method. In this paper, we propose a new method of estimating vessel diameter using direction codes and position informs:ion without detecting centerline. Since this method detects the vessel boundary and direction code at d same time, it simplifies the procedure and reduces execution time in estimating the vessel diameter. Compared to a method that automatically estimates the vessel diAmeter uslng centerline, our method provides improved accuracy in image with poor contrast, branching or obstructed vessels. Also, this provides a good compression of boundary description, because each direction code element can be coded with 3 bits only, instead of the 4 bytes required for the storage of the coordinates of each border pixel. Our experiments demonstrate the usefulness of the technique using direction code for quantitative analysis of coronary angiography Experimental results Justify the validity of the proposed method.

• Journal of Biomedical Engineering Research
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• v.30 no.5
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• pp.412-417
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• 2009

The purpose of this study was to assess the ability of this device during clinically important episodes of extravasation. The extravasation detection accessory (EDA) system was based of infrared ray with detection sensor, an amplifier, alarm device, receiver, cable and a computer based system. This study was a prospective, observational study in which the EDA system was used to monitor the automated mechanical injection of contrast media. Three hundred patients referred for contrast media enhanced body computed tomography studied in a prospective, observation study in which the EDA system was used to identify and interrupt any injection associated with clinically important extravasation. There were 8 true-positive cases, 276 true-negative cases, 15 false-positive cases and 1 false-negative cases. The EDA system had a sensitivity of 88.8% and a specificity of 94.8% for the detection of clinically important extravasation. The EDA system had good sensitivity for the detection of clinically important extravasation and the EDA system has the clinical potential for the early detection of extravasation of the contrast medium that is administered with power injectors.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.1041-1043
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• 2015

본 논문은 저선량 흉부 CT 영상을 활용하여 패결절을 자동으로 검출하는 알고리즘에 관한 연구내용을 담고 있다. 폐 결절 자동 검출을 위해 폐 CT 영상 내에 폐결절의 가지고 있는 특징들 중, 이동성 및 기하학적 특징을 가지고 폐혈관과 폐결절을 구분하였다. 실험한 영상은 폐결절이 없는 정상환자군을 가지고 실시 하였으며, 그 결과 4.4False Positive / Scan이 발생하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.636-638
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• 2022

This paper is a study to apply CNN(Convolution Neural Network) to fundus images for identifying glaucoma. Fundus images are evaluated in the field of medical diagnosis detection, which are diagnosing of blood vessels and nerve tissues, retina damage, various cardiovascular diseases and dementia. For the experiment, using normal image set and glaucoma image set, two types of image set are classifed by using AlexNet. The result performs that glaucoma with abnormalities are activated and characterized in feature map.

• Korean Journal of Optics and Photonics
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• v.26 no.1
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• pp.23-29
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• 2015

In this paper, we propose a microscope system for detecting both a tumor and blood vessels in brain tumor surgery as fluorescence images by using multiple light sources and a beam-splitter module. The proposed method displays fluorescent images of the tumor and blood vessels on the same display device and also provides accurate information about them to the operator. To acquire a fluorescence image, we utilized 5-ALA (5-aminolevulinic acid) for the tumor and ICG (Indocyanine green) for blood vessels, and we used a beam-splitter module combined with a microscope for simultaneous detection of both. The beam-splitter module showed the best performance at 600 nm for 5-ALA and above 800 nm for ICG. The beam-splitter is flexible to enable diverse objective setups and designed to mount a filter easily, so beam-splitter and filter can be changed as needed, and other fluorescent dyes besides 5-ALA and ICG are available. The fluorescent images of the tumor and the blood vessels can be displayed on the same monitor through the beam-splitter module with a CCD camera. For ICG, a CCD that can detect the near-infrared region is needed. This system provides the acquired fluorescent image to an operator in real time, matching it to the original image through a similarity transform.

• Journal of agricultural medicine and community health
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• v.27 no.2
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• pp.67-73
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• 2002

집쥐가 인체 기생충 전파에 어느 정도의 역할을 하는지 그 양상을 밝히고자 전라북도 남원, 익산지역에서 포획한 집쥐의 체내 기생충 감염상을 조사하였다. 섬진강 상류 남원지역에서 32마리, 만경강 중류 익산지역에서 53마리를 채집하여 총 85마리였고, 종별로는 곰쥐(Rattus rattus) 28마리, 시궁쥐(Rattus norvegicus) 57마리였다. 결과를 요약하면 다음과 같다. 1. 남원, 익산지역의 집쥐 85마리 중 71마리(83.5%)에서 체내 기생충이 검출되었다. 2. 폐장이 회수되었던 집쥐 74마리 중 35마리(47.3%)에서 폐장에 기생하는 조직 기생충인 폐포자충(Pneumocystis carinii)이 검출되었다. 3. 전체 85마리의 가로막에서 선모충(Trichinella spiralis)을 조사하였고, 폐심장 혈관계에서 광동주혈선충(Angiostrongylus cantonensis)을 조사하였으나 한 예도 검출하지 못하였다. 4. 간을 조사한 바 85마리 중 간모세선충(Capillaria hepatica) 22례(25.9%), Taenia taeniaeformis의 유충(Cysticercus fasciolaris) 9례(10.6%), 간흡충(Clonorchis sinensis) 1례(1.2%)가 검출되었다. 5. 장내용물을 조사 한 바 85 마리 중 50례(58.9%)에서 윤충 및 원충이 검출되었다. 윤충은 쥐조충(Hymenolepis diminuta), 극구흡충류(Echinostoma sp.), 쥐요충류(Syphacia sp.), 분신충류(Strongyloides sp.) 등이었고 원충은 대장아메바(Entamoeba coli) 등이었다. 이상의 결과에서 인수공통 질환을 일으킬 수 있는 폐포자충, 쥐조충, 간흡충 등이 집쥐에 감염되어 있어 철저한 집쥐 관리가 요망된다.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.345-350
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• 2018

This study is an algorithm for detecting vein pattern features important for finger vein recognition. The feature detection algorithm is important because it greatly affects recognition results in pattern recognition. The recognition rate is degraded because the reference is changed according to the finger position change. In addition, the image obtained by irradiating the finger with infrared light is difficult to separate the image background and the blood vessel pattern, and the detection time is increased because the image preprocessing process is performed. For this purpose, the presented algorithm can be performed without image preprocessing, and the detection time can be reduced. SWDA (Down Slope Trace Waveform) algorithm is applied to the finger vein images to detect the fingertip position and vein pattern. Because of the low infrared transmittance, relatively dark vein images can be detected with minimal detection error. In addition, the fingertip position can be used as a reference in the classification stage to compensate the decrease in the recognition rate. If we apply algorithms proposed to various recognition fields such as palm and wrist, it is expected that it will contribute to improvement of biometric feature detection accuracy and reduction of recognition performance time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.3029-3034
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• 2014

The paper describes the scleral diagnostic system implementation for human eyes by using the scleral color code and vessels sign pattern code generations. The system is based on the high performance DSP image signal processor, programmable gain control for preprocessing and RISC SD frames storage. RGB image signals are optimized by PGC, the edge image is detected form the gray image converted. The processing algorithms are executed by scleral color code generation and scleral vessels sign pattern code creation for discriminating and matching. The scleral symptomatic color code is generated by YCbCr values at memory map tolerated and the vessel sign pattern code is created by digitizing the 24 clock and 13 ring zones, overlay matching and tolerances. The experimental results for performance are that the system runs 40ms, and the color and pattern for diagnostic errors are around 20% and 24% on average. The system and technique enable a scleral diagnosis with subdividing the patterns and patient database.

• 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 the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.951-956
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• 2011

Coronary angiography technology is usually used for examining or treating coronary artery stenosis. Especially, when a cardiologist inserts catheter into the heart blood vessel, the catheter path detection system is needed because the cardiologist has difficulty in not damaging vessel. Recently, to reduce this difficulty, many searchers have been working for the various image processing technologies, such as vessel edge detection, optimal threshold method, etc. However the results of these searches are showing different performances depend on the contrast and quality of images. Therefore, this study for the coronary angiography suggests a novel algorithm to avoid these problems. The suggested algorithm consists of multi-sampling, interpolation, threshold method, and fault points elimination. To evaluate the performance of the proposed method, we used several angiographic images in experimentation, and we found that the proposed method is effective for detecting the catheter insertion path.