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Deep Convolutional Neural Network for Melanoma Detection using Dermoscopy Images. 2020

Kaur R, and GholamHosseini H, and Sinha R

Developing a fast and accurate classifier is an important part of a computer-aided diagnosis system for skin cancer. Melanoma is the most dangerous form of skin cancer which has a high mortality rate. Early detection and prognosis of melanoma can improve survival rates. In this paper, we propose a deep convolutional neural network for automated melanoma detection that is scalable to accommodate a variety of hardware and software constraints. Dermoscopic skin images collected from open sources were used for training the network. The trained network was then tested on a dataset of 2150 malignant or benign images. Overall, the classifier achieved high average values for accuracy, sensitivity, and specificity of 82.95%, 82.99%, and 83.89% respectively. It outperfomed other exisitng networks using the same dataset.

UI MeSH Term Description Entries
D008545 Melanoma A malignant neoplasm derived from cells that are capable of forming melanin, which may occur in the skin of any part of the body, in the eye, or, rarely, in the mucous membranes of the genitalia, anus, oral cavity, or other sites. It occurs mostly in adults and may originate de novo or from a pigmented nevus or malignant lentigo. Melanomas frequently metastasize widely, and the regional lymph nodes, liver, lungs, and brain are likely to be involved. The incidence of malignant skin melanomas is rising rapidly in all parts of the world. (Stedman, 25th ed; from Rook et al., Textbook of Dermatology, 4th ed, p2445) Malignant Melanoma,Malignant Melanomas,Melanoma, Malignant,Melanomas,Melanomas, Malignant
D003936 Diagnosis, Computer-Assisted Application of computer programs designed to assist the physician in solving a diagnostic problem. Computer-Assisted Diagnosis,Computer Assisted Diagnosis,Computer-Assisted Diagnoses,Diagnoses, Computer-Assisted,Diagnosis, Computer Assisted
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012878 Skin Neoplasms Tumors or cancer of the SKIN. Cancer of Skin,Skin Cancer,Cancer of the Skin,Neoplasms, Skin,Cancer, Skin,Cancers, Skin,Neoplasm, Skin,Skin Cancers,Skin Neoplasm
D016571 Neural Networks, Computer A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming. Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D046169 Dermoscopy A noninvasive technique that enables direct microscopic examination of the surface and architecture of the SKIN. Dermatoscopy,Epiluminescence Microscopy,Skin Surface Microscopy,Dermatoscopies,Dermoscopies,Epiluminescence Microscopies,Microscopies, Epiluminescence,Microscopies, Skin Surface,Microscopy, Epiluminescence,Microscopy, Skin Surface,Skin Surface Microscopies,Surface Microscopies, Skin,Surface Microscopy, Skin

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