Lesion Classification Using Convolutional Neural Network

  • Mayank SharmaEmail author
  • Aishwarya Bhave
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)


Malignant melanoma is uncommon in India as compared to the Western nations. However, its growth in recent years has been significant. Early detection of malignant skin lesions can help in proper cure. All recent works on automated classification of skin lesions generate a set of features based on the lesion segment such as lesion diameter and texture. The lesions are then classified into malignant and benign classes based on these features. In our work, we use convolutional neural networks (CNNs) with LeNet architecture in order to automate the feature extraction and selection process. We classify skin lesions in binary class of malignant and benign using ISBI 2016 and PH2 data set with an accuracy of 75% and 97.91%, respectively.


Skin lesion Skin lesion classification Convolutional neural network Deep learning Malignant melanoma 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.National Institute of Technology RaipurRaipurIndia

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