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Overview of Advanced Computer Vision Systems for Skin Lesions Characterization. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 13, NO. 5, SEPTEMBER 2009 Ilias Maglogiannis , Member, IEEE , and Charalampos N. Doukas , Student Member, IEEE Presentor: 陳麒文. Outline.
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Overview of Advanced Computer Vision Systemsfor Skin Lesions Characterization IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 13, NO. 5, SEPTEMBER 2009 Ilias Maglogiannis, Member, IEEE, and Charalampos N. Doukas, Student Member, IEEE Presentor: 陳麒文
Outline • Skin cancer back- Ground information • Materials and methods • Image Acquisition Techniques • Definition of Features for the Classification of Skin Lesions • Skin lesion classification methods • Results
Definition of Features for the Classification of Skin Lesions • ABCD Rule • pattern analysis • Menzies method • seven-point checklist; • texture analysis
ABCD rules • asymmetry • border • color • differential structures
Pattern analysis • Menzies method • Seven-point check list • atypical pigment network, blue-whitish veil, atypical vascular pattern • irregular streaks, irregular dots/globules, irregular blotches, and regression structures • Texture analysis
SKIN LESION CLASSIFICATION METHODS • Learning Phase • statistical • Neural networks • support vector machine (SVM) • adaptive wavelet-transform-based tree-structure classification (ADWAT) • Testing Phase
Feature selection • The success of image recognition depends on the correct selection of the features => optimization problem • heuristic strategies, greedy or genetic algorithms • strategies from statistical pattern recognition • XVAL, LOO, SFFS, SBFS, PCA, GSFS
Conclusion • It is often difficult to differentiate early melanoma from other benign skin lesions even for experienced • It is even more difficult for primary care physicians and general practitioners • The early diagnosis of skin cancer is important for the therapeutic procedure and reducing mortality rates. • Most remarkable features have been surveyed in this paper • Cost of a simple CDSS for skin assessment is low • Standardization of all steps in the CDSS procedure from the image acquisition until the feature extraction and the classification stages is considered essential