Automated Skin Lesion Detection towards Melanoma
نویسندگان
چکیده
منابع مشابه
Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network
Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is v...
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Dermoscopy image detection stays a tough task due to the weak distinguishable property of the object.Although the deep convolution neural network signifigantly boosted the performance on prevelance computer vision tasks in recent years,there remains a room to explore more robust and precise models to the problem of low contrast image segmentation.Towards the challenge of Lesion Segmentation in ...
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Melanoma spreads by metastasis, and therefore it has to be very fatal. A system to prevent this type of skin cancer, is expected and is highly in demand. It is important that excess exposure to radiation from the sun to mark gradually eroded by melanin in the skin. Furthermore, such radiation penetrate into the skin, thereby destroying the melanocytes. Melanomas are asymmetrical and have irregu...
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Developing automatic diagnostic tools for the early detection of skin cancer lesions in dermoscopic images can help to reduce melanoma-induced mortality. Image segmentation is a key step in the automated skin lesion diagnosis pipeline. In this paper, a fast and fully-automatic algorithm for skin lesion segmentation in dermoscopic images is presented. Delaunay Triangulation is used to extract a ...
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ژورنال
عنوان ژورنال: ICST Transactions on Scalable Information Systems
سال: 2018
ISSN: 2032-9407
DOI: 10.4108/eai.29-7-2019.159800