Artículo
Does a Previous Segmentation Improve the Automatic Detection of Basal Cell Carcinoma Using Deep Neural Networks?
Autor/es | Vélez, Paulina
Miranda, Manuel Serrano Gotarredona, María del Carmen Acha Piñero, Begoña |
Departamento | Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones |
Fecha de publicación | 2022-02 |
Fecha de depósito | 2022-03-23 |
Publicado en |
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Resumen | Basal Cell Carcinoma (BCC) is the most frequent skin cancer and its increasing incidence is
producing a high overload in dermatology services. In this sense, it is convenient to aid physicians
in detecting it soon. Thus, ... Basal Cell Carcinoma (BCC) is the most frequent skin cancer and its increasing incidence is producing a high overload in dermatology services. In this sense, it is convenient to aid physicians in detecting it soon. Thus, in this paper, we propose a tool for the detection of BCC to provide a prioritization in the teledermatology consultation. Firstly, we analyze if a previous segmentation of the lesion improves the ulterior classification of the lesion. Secondly, we analyze three deep neural networks and ensemble architectures to distinguish between BCC and nevus, and BCC and other skin lesions. The best segmentation results are obtained with a SegNet deep neural network. A 98% accuracy for distinguishing BCC from nevus and a 95% accuracy classifying BCC vs. all lesions have been obtained. The proposed algorithm outperforms the winner of the challenge ISIC 2019 in almost all the metrics. Finally, we can conclude that when deep neural networks are used to classify, a previous segmentation of the lesion does not improve the classification results. Likewise, the ensemble of different neural network configurations improves the classification performance compared with individual neural network classifiers. Regarding the segmentation step, supervised deep learning-based methods outperform unsupervised ones |
Identificador del proyecto | DPI2016-81103-R
US-1381640 EJ3-83-1 |
Cita | Vélez, P., Miranda, M., Serrano, C. y Acha, B. (2022). Does a Previous Segmentation Improve the Automatic Detection of Basal Cell Carcinoma Using Deep Neural Networks?. Applied Sciences, 12 (4), Article number 2092. |
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