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A Comparative Study on Left and Right Endocardium Segmentation using Gradient Vector Field and Adaptive Diffusion Flow Algorithms
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- 발행기관
- 보안공학연구지원센터(IJBSBT) 바로가기
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- 간행물
- International Journal of Bio-Science and Bio-Technology SCOPUS 바로가기
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- 통권
- Vol.8 No.1 (2016.02)바로가기
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- 페이지
- pp.105-120
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A263360
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- The cardiac Magnetic Resonance Imaging (MRI) provides high resolution images of the heart without radiation exposure. It is an excellent noninvasive test used by radiologist for proper detection of heart diseases. The manual segmentation of left ventricle in cine short axis MRI sequences takes an ample amount of time as compared to semi-automated segmentation. In Gradient Vector Flow (GVF) model certain barriers hinder the performance such as weak edge detection, high computational time, limited capture range and its ambiguity with other parameters. In this paper segmentation of Endocardium is carried out on multistage MRI frames Using Adaptive Diffusion flow (ADF) model. This deformable model was tested on large scale number of Cardiac MRI images. We replace the smoothening energy term in GVF with active hyper-surface harmonic minimal function in order to avoid possible leakage at weak edges. The use of harmonic maps is adjusted in accordance with image characteristics. We also assimilate infinite Laplace function to move active contours into narrow concave sections. Experimental results and collation with GVF are presented in this paper which reveals several good results based on extraction of endocardium tissue from left and right ventricle, including less computational time, noise robustness and weak edge preserving on Cardiac MR Images.
목차
Abstract
1. Introduction
2. Background
2.1. Gradient Vector Field Active Contour Model (GVF Snakes)
2.2. GVF Limitations
2.3. Endocardium Segmentation: Survey
3. Methodology
3.1. Hyper-surface Harmonic Minimal Functional Analysis
3.2. Infinite Laplace Functional Analysis
3.3. Adaptive Diffusion Flow Snake (ADF)
3.4. Flowchart of Algorithm
4. Results and Analysis
4.1. Seed Points Initialization and Curve Evolution
4.2. Segmented ADF Cardiac MRI Outputs
4.3. Comparative Results of ADF with GVF
4.4. Associated Manual and Semi-Automated Segmentation
4.5. Computation Time
5. Conclusion
References
키워드
Endocardium segmentation Snakes Magnetic Resonance imaging (MRI) Active contours Adaptive diffusion flow (ADF) Gradient vector flow (GVF).저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJBSBT) [Science & Engineering Research Support Center, Republic of Korea(IJBSBT)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
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- 간행물명
- International Journal of Bio-Science and Bio-Technology
- 간기
- 격월간
- pISSN
- 2233-7849
- 수록기간
- 2009~2016
- 등재여부
- SCOPUS
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Bio-Science and Bio-Technology Vol.8 No.1
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