University of Hertfordshire

By the same authors

Pigmented skin lesions classification using convolutional neural networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Prasitthichai Naronglerdrit
  • Iosif Mporas
  • Isidoros Perikos
  • Michael Paraskevas
View graph of relations
Original languageEnglish
Title of host publicationProceedings of the International Conference on "Biomedical Innovations and Applications"
Subtitle of host publicationBIA 2019
EditorsValentina Markova, Todor Ganchev
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781728147543
ISBN (Print)9781728147550
DOIs
Publication statusPublished - Nov 2019
Event2019 International Conference on Biomedical Innovations and Applications, BIA 2019 - Varna, Bulgaria
Duration: 8 Nov 20199 Nov 2019

Publication series

NameProceedings of the International Conference on "Biomedical Innovations and Applications", BIA 2019

Conference

Conference2019 International Conference on Biomedical Innovations and Applications, BIA 2019
CountryBulgaria
CityVarna
Period8/11/199/11/19

Abstract

In this paper we present an architecture for classification of pigmented skin lesions from dermatoscopic images. The architecture is using image pre-processing for natural hair removal and image segmentation for extraction of the skin lesion area. The segmented images were processed by a convolutional neural network classifier. The training process was done by using the Keras and TensorFlow python packets with CUDA supported. The best performance was achieved by a convolutional neural network architecture with three convolution layers and the classification accuracy was equal to 76.83%.

ID: 20230106