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Melanoma detection by analysis of clinical images using convolutional neural network

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Mar 9, 2017

E Nasr-EsfahaniK Najarian

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Abstract

Melanoma, most threatening type of skin cancer, is on the rise. In this paper an implementation of a deep-learning system on a computer server, equipped with graphic processing unit (GPU), is proposed for detection of melanoma lesions. Clinical (non-dermoscopic) images are used in the p...read more

Mentioned in this Paper

Malignant Neoplasm of Skin
Biological Neural Networks
Classification
Nevus
Cutaneous Melanoma
Computer Assisted Diagnosis
Dermoscopy
Morphologic Artifacts
Neural Stem Cells
Neural Network Simulation
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Melanoma detection by analysis of clinical images using convolutional neural network

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Mar 9, 2017

E Nasr-EsfahaniK Najarian

PMID: 28268581

DOI: 10.1109/embc.2016.7590963

Abstract

Melanoma, most threatening type of skin cancer, is on the rise. In this paper an implementation of a deep-learning system on a computer server, equipped with graphic processing unit (GPU), is proposed for detection of melanoma lesions. Clinical (non-dermoscopic) images are used in the p...read more

Mentioned in this Paper

Malignant Neoplasm of Skin
Biological Neural Networks
Classification
Nevus
Cutaneous Melanoma
Computer Assisted Diagnosis
Dermoscopy
Morphologic Artifacts
Neural Stem Cells
Neural Network Simulation

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Paper Details
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