Abstract
Using Reflectance Confocal Microscopy (RCM) for lentigo diagnosis is today considered essential. Indeed, RCM allows fast data acquisition with a high spatial resolution of the skin. In this paper, we use a deep convolutional neural network (CNN) to perform RCM image classification in order to detect lentigo. The proposed method relies on an InceptionV3 architecture combined with data augmentation and transfer learning. The method is validated on RCM data and shows very efficient detection performance with more than 98% of accuracy.
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CITATION STYLE
Zorgui, S., Chaabene, S., Bouaziz, B., Batatia, H., & Chaari, L. (2020). A Convolutional Neural Network for Lentigo Diagnosis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12157 LNCS, pp. 89–99). Springer. https://doi.org/10.1007/978-3-030-51517-1_8
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