Temporal Segmentation of Digital Colposcopies

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2015

Autores

Kelwin Fernandes (Autor) Outra; Jaime S Cardoso (Autor) FEUP; Jessica Fernandes (Autor) Outra

Ata de Conferência Internacional

Título: PATTERN RECOGNITION AND IMAGE ANALYSIS (IBPRIA 2015)

Páginas: 262-271

7th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)

Santiago de Compostela, SPAIN, JUN 17-19, 2015

Indexação

ISI Web of Knowledge - 11 Citações

Scopus - 13 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-00G-EHZ

DOI: 10.1007/978-3-319-19390-8_30

Abstract (EN): Cervical cancer remains a significant cause of mortality in low-income countries. Digital colposcopy is a promising and inexpensive technology for the detection of cervical intraepithelial neoplasia. However, diagnostic sensitivity varies widely depending on the doctor expertise. Therefore, automation of this process is needed in both, detection and visualization. Colposcopies cover four steps: macroscopic view with magnifier white light, observation under green light, Hinselmann and Schiller. Also, there are transition intervals where the specialist manipulates the observed area. In this paper, we focus on the temporal segmentation of the video in these steps. Using our solution, physicians may focus on the step of interest and lesion detection tools can determine the interval to diagnose. We solved the temporal segmentation problem using Weighted Automata. Images were described by their chromacity histograms and labeled using a KNN classifier with a precision of 97%. Transition frames were recognized with a precision of 91 %.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10