Pectoral muscle detection in mammograms based on the shortest path with endpoints learnt by SVMs

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2010

Autores

Ines Domingues (Autor) Outra; Jaime S Cardoso (Autor) FEUP; Igor Amaral (Autor) Outra; Ines Moreira (Autor) Outra; Pedro Passarinho (Autor) Outra; Joao Santa Comba (Autor) Outra; Ricardo Correia (Autor) FMUP; Maria J Cardoso (Autor) Outra

Ata de Conferência Internacional

Título: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Páginas: 3158-3161

2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Buenos Aires, 31 August 2010 through 4 September 2010

Indexação

ISI Proceedings

ISI Web of Knowledge - 12 Citações

Scopus - 19 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Biotecnologia ambiental

Outras Informações

ID Authenticus: P-018-0W3

DOI: 10.1109/iembs.2010.5627168

Abstract (EN): Automatic pectoral muscle removal on mediolateral oblique view of mammogram is an essential step for many mammographic processing algorithms. However, the wide variability in the position of the muscle contour, together with the similarity between in muscle and breast tissues makes the detection a difficult task. In this paper, we propose a two step procedure to detect the muscle contour. In a first step, the endpoints of the contour are predicted with a pair of support vector regression models; one model is trained to predict the intersection point of the contour with the top row while the other is designed for the prediction of the endpoint of the contour on the left column. Next, the muscle contour is computed as the shortest path between the two endpoints. A comprehensive comparison with manually-drawn contours reveals the strength of the proposed method. © 2010 IEEE.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 4