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EISCR : Efficient Image Segmentation using Cluster Representatives for Carcinoma Images
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- 발행기관
- 보안공학연구지원센터(IJHIT) 바로가기
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- 간행물
- International Journal of Hybrid Information Technology 바로가기
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- 통권
- Vol.9 No.3 (2016.03)바로가기
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- 페이지
- pp.399-406
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A270805
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Medical care requires intensively Image segmentation which a significant tool used to extract origin of interest from the background. Different segmentation techniques are deployed in medical images leading to an essential developments in both diagnosis and detection process. Such development has managed to assist specialists and doctors specified in the medical care system to diagnose the patients accurately. This study will propose a more developed methodology via incorporating cluster representatives and second derivative filter technique on Carcinoma image. The conventional segmentation algorithm is widely deployed in medical care image, in spite of its advantages; being able to produce a complete division of the image, but it contains major drawbacks represented by the over-segmentations and sensitivity to false edges. This study will expose these major problems of the conventional algorithm and fixing these problems via deploying Cluster Representatives; that uses a set of pixels as representatives that represent the clusters and producing advanced results. The other process deployed is a second derivative filter applied to the segmented image resulting of the demolition of unwanted region from the image. Nevertheless, results of this study has proved that the number of partitions in medical care images are much fewer when comparing partitions produced by deploying the traditional algorithm deployed in medical care images. Such result will assist experts to easily diagnose health problems in a more accurate measure.
목차
Abstract
1. Introduction
2. Related Work
3. K-Means Clustering Algorithm
4. Laplacian of Gaussian filter (LoG)
5. Difference of Gaussians (DOG)
6. Proposed Algorithm: Cluster formation using EISCR Algorithm
7. Results
8. Conclusion
References
저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJHIT) [Science & Engineering Research Support Center, Republic of Korea(IJHIT)]
- 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 Hybrid Information Technology
- 간기
- 격월간
- pISSN
- 1738-9968
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Hybrid Information Technology Vol.9 No.3
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