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Classification of dermatological images using advanced clustering techniques
- Source :
- 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
- Publication Year :
- 2010
- Publisher :
- IEEE, 2010.
-
Abstract
- Computer vision-based diagnosis systems have been widely used in dermatology, aiming at the early detection of skin cancer and more specifically the recognition of malignant melanoma tumor. This paper proposes a novel clustering technique for the characterization and categorization of pigmented skin lesions in dermatological images. Appropriate image processing techniques (i.e. segmentation, border detection, color and texture processing) are utilized for feature extraction. The proposed method uses Principal Component Analysis and is considered appropriate, since it is suitable for problems with high dimensional data. Initial experimental results have proved the superiority of this method against traditional ones.
- Subjects :
- Clustering high-dimensional data
Skin Neoplasms
Computer science
Kernel density estimation
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Image processing
Image texture
Image Processing, Computer-Assisted
medicine
Cluster Analysis
Humans
Computer vision
Segmentation
Cluster analysis
Melanoma
Contextual image classification
business.industry
Cancer
Pattern recognition
Image segmentation
medicine.disease
Categorization
Principal component analysis
Artificial intelligence
Skin cancer
business
Algorithms
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology
- Accession number :
- edsair.doi.dedup.....6352a32be469f4d1513da1ba24e1d2f1