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Diagnosis of Skin Lesions Based on Dermoscopic Images Using Image Processing Techniques
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- 발행기관
- 보안공학연구지원센터(IJSIP) 바로가기
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- 간행물
- International Journal of Signal Processing, Image Processing and Pattern Recognition 바로가기
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- 통권
- Vol.9 No.9 (2016.09)바로가기
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- 페이지
- pp.189-204
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A284976
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Great effort has been put into the development of diagnosis methods for the most dangerous type of skin diseases - Melanoma. This paper aims to develop a prototype capable of segment and classify skin lesions in dermoscopy images based on ABCD rule. The proposed work is divided into four distinct stages: 1) Pre-processing, consists of filtering and contrast enhancing techniques. 2) Segmentation, thresholding and statistical properties are computed to localize the lesion. 3) Features extraction, Asymmetry is calculated by averaging the calculated results of the two methods: Entropy and Bi-fold. Border irregularity is calculated by accumulate the statistical scores of the eight segments of the segmented lesion. Color feature is calculated among the existence of six candidate colors: white, black, red, light-brown, dark-brown, and blue-gray. Diameter is measured by the conversion operation from the total number of pixels in the greatest diameter into millimeter (mm). 4) Classification, the summation of the four extracted feature scores multiplied by their weights to yield a total dermoscopy score (TDS); hence, the lesion is classified into benign, suspicious, or malignant. The prototype is implemented in MATLAB and the dataset used consists of 200 dermoscopic images from Hospital Pedro Hispano, Matosinhos. The achieved results shows an acceptable performance rates, an accuracy 90%, sensitivity 85%, and specificity 92.22%.
목차
Abstract
1. Introduction
2. Related Works
3. Research Methodology
3.1. Preprocessing Stage
3.2. Segmentation Stage
3.3. Features Extraction Stage
3.4. Classification Stage
4. Experimental Results and Discussion
4.1. Hardware and Software Specifications
4.2. Dataset
4.3. Implementation of ABCD Rule
4.4. Discussion
5. Conclusion and Future Work
References
키워드
Dermoscopy ABCD rule Segmentation Feature extraction Classification저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
- 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 Signal Processing, Image Processing and Pattern Recognition
- 간기
- 격월간
- pISSN
- 2005-4254
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9 No.9
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