Joint Capsule Segmentation in Ultrasound Images of the Metacarpophalangeal Joint using Convolutional Neural Networks

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2019

Autores

Martins, N (Autor) Outra; Costa, E (Autor) Outra; Veiga, D (Autor) Outra; Ferreira, M (Autor) Outra; Coimbra, M (Autor) FCUP

Ata de Conferência Internacional

Título: 6th IEEE Portuguese Meeting on Bioengineering, ENBENG 2019 - Proceedings

6th IEEE Portuguese Meeting on Bioengineering, ENBENG 2019

22 February 2019 through 23 February 2019

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-00Q-K19

DOI: 10.1109/enbeng.2019.8692489

Abstract (EN): This work addresses the automatic segmentation of the joint capsule in ultrasound images of the metacarpophalangeal joint using an adapted version of the well known UNet model. These images are used in the diagnosis of rheumatic diseases, one of the main causes of impairment and pain in developed countries. The identification of the joint capsule gives important clues about the presence or Rheumatoid Arthritis. This structure can be used to extract metrics to help quantify the disease stage and progression. The solution proposed here has the potential to reduce the burden on the radiologists as well as the subjectivity of the diagnosis by providing quantitative measurements, such as the synovitis area. The proposed approach was compared with two other works present in the literature. Results show that our solution outperforms the two reference methods with 90% of the joint capsules identified with a DICE higher than 0.67.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 4