Deep Convolutional Neural Network Ensembles For Multi-Classification of Skin Lesions From Dermoscopic and Clinical Images

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2020

Autores

Reisinho, J (Autor) Outra; Coimbra, M (Autor) FCUP; Renna, F (Autor) FCUP

Ata de Conferência Internacional

Título: 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2020, Montreal, QC, Canada, July 20-24, 2020

Páginas: 1940-1943

Indexação

ISI Web of Knowledge - 2 Citações

Scopus - 5 Citações

Outras Informações

ID Authenticus: P-00S-S4F

DOI: 10.1109/embc44109.2020.9176411

Abstract (EN): In this paper, we consider the problem of classifying skin lesions into multiple classes using both dermoscopic and clinical images. Different convolutional neural network architectures are considered for this task and a novel ensemble scheme is proposed, which makes use of a progressive transfer learning strategy. The proposed approach is tested over a dataset of 4000 images containing both dermoscopic and clinical examples and it is shown to achieve an average specificity of 93.3% and an average sensitivity of 79.9% in discriminating skin lesions belonging to four different classes.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 4