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Abstract:
Skin cancer is one of the most frequently encountered types of cancer in the Western world. According to the Skin Cancer foundation Statistics, one in every five Americans develops skin cancer during his/her lifetime. Today, the incurability of advanced cutaneous melanoma raises the importance of its early detection. Since the differentiation of early melanoma from other pigmented skin lesions is not a trivial task, even for experienced dermatologists, computer aided diagnosis could become an important tool for reducing the mortality rate of this highly malignant cancer type. In this thesis, a computer aided diagnosis system based on machine learning is proposed in order to support the clinical use of optical spectroscopy and dermatoscopy imaging techniques for skin lesions quantification and classification.
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Title: | PhD? Defense of Asad Safi: Towards Computer-Aided Diagnostic of Pigmented Skin Lesions |
Date: | 23 May 2012 |
Location: | Institut für Medizinische Statistik und Epidemiologie, Building 523, Room 2.2 „Besprechungsraum“ Klinikum rechts der Isar, |
Abstract: | Skin cancer is one of the most frequently encountered types of cancer in the Western world. According to the Skin Cancer foundation Statistics, one in every five Americans develops skin cancer during his/her lifetime. Today, the incurability of advanced cutaneous melanoma raises the importance of its early detection. Since the differentiation of early melanoma from other pigmented skin lesions is not a trivial task, even for experienced dermatologists, computer aided diagnosis could become an important tool for reducing the mortality rate of this highly malignant cancer type. In this thesis, a computer aided diagnosis system based on machine learning is proposed in order to support the clinical use of optical spectroscopy and dermatoscopy imaging techniques for skin lesions quantification and classification. |
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Type: | News |
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