Automatic Detection of Melanoma and Non Melanoma Skin Cancer: Using Classification Framework of Neural Network
نویسندگان
چکیده
منابع مشابه
Non-melanoma skin cancer diagnosis with a convolutional neural network
Background: The most common types of non-melanoma skin cancer are basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). AKIEC -Actinic keratoses (Solar keratoses) and intraepithelial carcinoma (Bowen’s disease)- are common non-invasive precursors of SCC, which may progress to invasive SCC, if left untreated. Due to the importance of early detection in cancer treatment, this study aimed...
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Melanoma is the most dangerous skin cancer. It should be diagnosed early because of its aggressiveness. To diagnose melanoma earlier, skin lesion should be segmented accurately. To reduce the cost for specialists to screen every patient, there is a need of automated melanoma prescreening system to diagnose melanoma using images acquired in digital cameras. In this frame work, an automated melan...
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Abstract Introduction: Non-melanoma scalp skin cancers (NMSCs) including squamous cell carcinomas (SCCs) and basal cell carcinomas (BCCs) are common. To manage such cancers, especially SCCs, more attention should be paid to their invasive characteristics. Mortality surveillance of SCCs and BCCs of scalp helps to choose proper approaches. Methods: The current retrospective, descriptive study w...
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Abstract Introduction: Non-melanoma scalp skin cancers (NMSCs) including squamous cell carcinomas (SCCs) and basal cell carcinomas (BCCs) are common. To manage such cancers, especially SCCs, more attention should be paid to their invasive characteristics. Mortality surveillance of SCCs and BCCs of scalp helps to choose proper approaches. Methods: The current retrospective, descriptive study w...
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ژورنال
عنوان ژورنال: International Journal of Modern Communication Technologies & Research (IJMCTR)
سال: 2018
ISSN: 2321-0850
DOI: 10.31873/ijmctr.6.6.40