• 제목/요약/키워드: Vascular segmentation

검색결과 17건 처리시간 0.03초

초음파 혈관 영상의 상호적 영상 분할 (Interactive image segmentation for ultrasound vascular imaging)

  • 이언석;김민기;하승한
    • 한국융합학회논문지
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    • 제3권4호
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    • pp.15-21
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    • 2012
  • 초음파 영상 진단 장치에서 획득한 데이터로부터 진단 객체를 추출하기 위한 영상 분할은 질병의 효과적인 진단을 위하여 필수적인 전처리 과정으로 인식되고 있으며, 지금까지 많은 분할 기법들이 연구되고 있다. 본 연구에서는 혈관 초음파 영상의 다양한 응용 및 진단법 개발을 위하여 기초 전처리과정으로서 graph cut 알고리즘에 의한 상호적인 영상분할법을 제시한다. 일반영상 및 혈관 초음파 영상에 대하여 전경(foreground)과 배경(background)의 제약조건을 주고 영상분할 처리하여, 원하는 object에 대한 분할 결과를 얻었다. 향후, 이러한 일련의 처리 과정이 실시간으로 처리되면 새로운 초음파 진단법으로 발전시켜 나갈 수 있을 것으로 사료된다.

ITK를 이용한 폐혈관 분할 (Pulmonary vascular Segmentation Using Insight Toolkit(ITK))

  • 신민준;김도연
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2011년도 추계학술대회
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    • pp.554-556
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    • 2011
  • 각종 폐혈관 질환의 발생에 따른 정확하고 빠른 진단의 필요성이 강조되었다. 몇 가지 폐혈관 조영술의 제약사항의 존재로 흉부 CT에 대한 영상 처리의 필요성을 인지하였고 의료 영상처리의 다양성을 위해 ITK를 이용한 폐혈관 분할을 제안하였다. 본 논문은 명암 값을 기반한 방법으로 두 단계의 폐 영역 분할과 혈관 분할의 과정을 수행한다. 각 단계로 폐 영역 분할은 영상 향상, 문턱치 값, 관심영역 잘라내기로 결과 영상을 획득하고 폐 혈관 분할은 획득된 폐 영역에 영역 채우기를 적용하여 얻는다. 분할된 폐혈관 영상을 바탕으로 3차원 시각화 영상을 획득하여 폐혈관에 대한 다양한 관점의 분석 및 진단이 가능할 것으로 판단된다.

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Segmentation of Arterial Vascular Anatomy around the Stomach based on the Region Growing Based Method

  • Kang, Jiwoo;Kim, Doyoung;Lee, Sanghoon
    • Journal of International Society for Simulation Surgery
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    • 제1권2호
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    • pp.75-79
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    • 2014
  • Purpose The region growing has a critical problem that it often extract vessels with unexpected objects such as a bone which has a similar intensity characteristics to the vessel. We propose the new method to extract arterial vascular anatomy around the stomach from the CTA volume without the post-processing. Materials and Methods Our method, which is also based on the region growing, requires the two seed points from the use. I automatically extracts perigastric arteries using the adaptive region growing method and it does not need any post-processing. Results The three region growing based methods are used to extract perigastric arteries - the conventional region growings with restrict and loose thresholds each and the proposed method. The 3D visualization from the result of our method shows our method extracted the all required arteries for gastric surgery. Conclusion By extracting perigastric arteries using the proposed method, over-segmentation problem that unexpected anatomical objects such as a rib or backbone are also segmented does not occurs anymore. The proposed method does not need to sensitively determine the thresholds of the similarity function. By visualizing the result, the preoperative simulation of arterial vascular anatomy around the stomach can be possible.

지역적 패치기반 보정기법을 활용한 2D X-ray 영상에서의 강인한 관상동맥 재연결 기법 (Robust Coronary Artery Segmentation in 2D X-ray Images using Local Patch-based Re-connection Methods)

  • 한경훈;전병환;김세근;장영걸;정성희;심학준;장혁재
    • 방송공학회논문지
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    • 제24권4호
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    • pp.592-601
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    • 2019
  • 관상동맥 시술을 위해 혈관 조영 X-선 영상은 시술 진단 및 보조에 유용하게 활용된다. 삼차원의 복잡한 구조를 가진 관상동맥을 이차원 X-선 영상에서 기존의 단일기법만을 사용하여 정확히 분할하는 것에 어려움이 있으며, 특히 혈관이 중간에 끊어지거나 말단부위혈관이 유실되는 현상으로부터 오차가 크게 발생하는 경향이 있었다. 이러한 문제를 해결하기 위하여 기존 단일기법으로 초기분할 단계를 거친 후, 초기분할결과를 기반으로 정교한 보정영역을 설정하는 단계, 보정영역을 대상으로 패치기반 지역보정을 수행하는 단계가 수행된다. 본 연구를 통해 끊긴 혈관을 보완한 분할 결과를 구할 수 있을 뿐만 아니라 미세혈관까지 포함하지 못한 참 값의 한계점을 해결할 수 있다. 또한, 존재하는 기존 관상동맥 분할방법들에 융합하여 추가적인 성능개선을 얻어낼 수 있다. 본 논문에서는 Fully convolutional network 기반 깊은 신경망 네트워크인 U-net을 활용하였으며, 제안된 보정방법을 융합하여 기존 U-net 단일 모델 대비 성능이 상당히 개선된다는 것을 실제 여러 환자들의 데이터 셋을 통하여 증명하였다.

Coronary Vessel Segmentation by Coarse-to-Fine Strategy using Otsu Algorithm and Decimation-Free Directional Filter Bank

  • Trinh, Tan Dat;Tran, Thieu Bao;Thuy, Le Nhi Lam;Shimizu, Ikuko;Kim, Jin Young;Bao, Pham The
    • 전기전자학회논문지
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    • 제23권2호
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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%.

컴퓨터 단층 촬영 영상에서의 폐혈관 분할 및 정제 (Pulmonary vascular Segmentation and Refinement On the CT Scans)

  • 신민준;김도연
    • 한국정보통신학회논문지
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    • 제16권3호
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    • pp.591-597
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    • 2012
  • 신체 주요 장기들에 대한 영상의 중요성이 커져감에 따라 향상된 의료 장비들이 등장하였으며, 획득된 영상에 대한 개선된 화질과 활용성에 기대가 높아지고 있다. 최근 향상된 영상분석 연구를 위해 MATLAB을 이용한 영상 처리의 빈도가 커져가는 것에 기인하여 MATLAB을 이용하여 폐혈관을 분할하였다. 본 논문은 3단계로 폐 영역 분할, 폐 혈관 분할과 3차원 연결성 검사로 수행된다. 분할된 폐 영역에서 문턱치 값을 사용하여 혈관을 분할하고, 2차원 정제 과정인 혈관 두께 분류를 수행한 후 3차원 정제 과정으로 3차원 연결성 검사를 적용하였다. MATLAB을 통한 영상 처리로 의료영상 처리의 다양성 측면과 신뢰성 향상에 기여하였고 흉부 CT 영상을 이용한 관련 연구의 기반이 되리라 판단된다.

양.한방 의료서비스 이용환자의 시장 세분화에 관한 연구 (Market Segmentation of Patient-Utilization in Oriental Medical Care and Western Medical Care)

  • 이선희;조희숙;최은영;최귀선;채유미
    • 보건행정학회지
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    • 제12권1호
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    • pp.125-143
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    • 2002
  • The objectives of this study were analysis of patient\`s characteristics and market segmentation in oriental medical care and western medical care. This study focused on medical utilization using Anderson's health utilization model. The source of data was 1998 National Health and Nutrition Survey which Korean Institute For Health and Social Affairs carried out. A stratified multistage probability sampling design was used in this survey. The analysis was conducted using the statistical software package SPSS version 10.0 and Answer Tree 2.1 which is one of data mining methodology. The results were as follows ; 1) 44.9% of respondents reported visiting oriental medical center within recent two weeks. 3.4% of them used oriental medical care. The group of age, kind of disease and medical expenditure are associated with the difference western and oriental medical utilization rate. 2) There were several factors related to utilization of oriental medical care according to decision tree. Especially, important factors that patient chose his medical center were kinds of disease, kinds of common medical use, and expenditure. 3) in the results of CART analysis, market of oriental medical care were classified by seven categories. The major groups who have a preference for oriental medicine were those musculo-skeletal, cerebra-vascular disease, or chronic headache patients, and they had a preference fur oriental medical care in common use. These results show that oriental and western medical market were divided into various areas by market segmentation.

생체 인식 인식 시스템을 위한 주의 인식 잔차 분할 (Attention Aware Residual U-Net for Biometrics Segmentation)

  • 앤디;이효종
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2022년도 추계학술발표대회
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    • pp.300-302
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    • 2022
  • Palm vein identification has attracted attention due to its distinct characteristics and excellent recognition accuracy. However, many contactless palm vein identification systems suffer from the issue of having low-quality palm images, resulting in degradation of recognition accuracy. This paper proposes the use of U-Net architecture to correctly segment the vascular blood vessel from palm images. Attention gate mechanism and residual block are also utilized to effectively learn the crucial features of a specific segmentation task. The experiments were conducted on CASIA dataset. Hessian-based Jerman filtering method is applied to label the palm vein patterns from the original images, then the network is trained to segment the palm vein features from the background noise. The proposed method has obtained 96.24 IoU coefficient and 98.09 dice coefficient.

Blood Vessel Enhancement by Directed Diffusion

  • Intajag, S.;Tipsuwanporn, V.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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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.

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New Seed Detection by Shape Analysis for Construction of Vascular Structures

  • Shim, Hack-Joon;Lee, Hyun-Joon;Yun, Il-Dong;Lee, Sang-Uk
    • 대한의용생체공학회:의공학회지
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    • 제31권6호
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    • pp.427-433
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    • 2010
  • Although tracking methods are efficient and popular for vessel segmentation, they require a seed to initiate an instance of tracking. In this paper, a new method to detect new seeds for tracking of arterial segments from CT angiography (CTA) and to construct a vascular structure is proposed. The proposed algorithm is based on shape analysis of connected components in a volume of interest around a vessel segment which was already extracted by tracking. The eigenvalues of the covariance matrix are used as the shape features for detection. The experimental results on actual clinical data showed that the results totally revealed the arterial tree not hindered by bone or veins. In visual comparison to a method which combines registration and subtraction of both pre-contrast and post-contrast CT volumes, the proposed method produced comparable results to the reference method and were confirmed of its feasibility for clinical use of reducing the cost and burden of patients.