Computational methods for pigmented skin lesion classification in images: review and future trends
نویسندگان
چکیده
منابع مشابه
Pigmented Skin Lesions Classification Using Dermatoscopic Images
In this paper we propose a machine learning approach to classify melanocytic lesions in malignant and benign from dermatoscopic images. The image database is composed of 433 benign lesions and 80 malignant melanoma. After an image pre-processing stage that includes hair removal filtering, each image is automatically segmented using well known image segmentation algorithms. Then, each lesion is ...
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BACKGROUND AND OBJECTIVES Because skin cancer affects millions of people worldwide, computational methods for the segmentation of pigmented skin lesions in images have been developed in order to assist dermatologists in their diagnosis. This paper aims to present a review of the current methods, and outline a comparative analysis with regards to several of the fundamental steps of image process...
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In this paper, we put forward a new pre-processing scheme for automatic analysis of dermoscopic images. Our contributions are two-fold. First, we present a procedure, an extension of previous approaches, which succeeds in removing confounding factors from dermoscopic images: these include shading induced by imaging non-flat skin surfaces and the effect of light-intensity falloff toward the edge...
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Background: With advances in medical imaging systems, digital dermoscopy has become one of the major imaging modalities in the analysis of skin lesions. Thus, automated segmentation or border detection has a great impact on the subsequent steps of skin cancer computer-aided diagnosis using demoscopy images. Since dermoscopy images suffer from artifacts such as shading and hair, there is a need ...
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ژورنال
عنوان ژورنال: Neural Computing and Applications
سال: 2016
ISSN: 0941-0643,1433-3058
DOI: 10.1007/s00521-016-2482-6