Contenido principal del artículo
Breast cancer is a priority public health problem due to its global magnitude and importance, that develops mainly in the glandular tissue. On mammography imaging, the presence of a large amount of glandular tissue could conceal lesions. Due to this, the estimation of glandular fraction (FG) is a tool that allows evaluating the risk of developing breast cancer. Having knowledge of the different tissues that constitute the anatomy of the breast (glandular, connective and adipose tissues), on a mammography image there are structures that should not be considered for the estimation of the FG, such as skin or pectoral muscle. In the clinical practice, a proper differentiation between glandular and connective tissues is a challenging task, and a discrimination of extra-mammary structures from glandular tissue is particularly difficult due to an intensity similarity. In this work, a strategy to properly isolate the principal breast tissues from the extra-mammary structures, and to perform a robust semi-automatic segmentation of glandular, connective and adipose tissues by using the K-means algorithm in order to provide a quantitative estimation of the mammary glandular fraction is presented. Additionally, a comparison with the Density-based Spatial Clustering of Applications with Noise (DBSCAN) and an empirical glandular fraction estimated by a clinical expert, to demonstrate the convenience of the strategy is made.
Detalles del artículo
DERECHOS DE AUTOR Y DERECHOS CONEXOS, las MEMORIAS CONGRESO NACIONAL DE INGENÍERIA BIOMÉDICA es una publicación editada por la Sociedad Mexicana de Ingeniería Biomédica A.C., Plaza Buenavista, núm. 2, Col. Buenavista, Delegación Cuauhtémoc, C.P. 06350, México, D.F., Tel. +52 (555) 574-4505, www.somib.org.mx, correo-e: firstname.lastname@example.org. Editor responsable: Elliot Vernet Saavedra. Reserva de Derechos al Uso Exclusivo No. 04-2015-011313082200-01, ISSN: 2395-8928, ambos otorgados por el Instituto Nacional de Derechos de Autor.