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Semiautomatic Snake-Based Segmentation of Solid Breast Nodules on Ultrasonography

2005; Springer Science+Business Media; Linguagem: Inglês

10.1007/11556985_60

1611-3349

Miguel Alemán-Flores, Patricia Alemán-Flores, Luis Álvarez, M. Belén Esteban-Sánchez, Rafael Fuentes-Pavón, José M. Santana-Montesdeoca,

Radiomics and Machine Learning in Medical Imaging

Ultrasonography plays a crucial role in the diagnosis of breast cancer. However, it is one of the most difficult types of images to segment and analyze. The presence of speckle noise and low contrast areas limits the success of most noise reduction filters and segmentation algorithms. In this paper, we propose a combination of different techniques which provide quite satisfactory results in the segmentation of breast tumors on ultrasonography. It is performed in a semiautomatic way, which eliminates the need for a manual delineation of the contour of the nodules. These techniques include the truncated median filter, a region-growing algorithm and active contours. Furthermore, this can be the initial phase for an exhaustive analysis of the diagnostic criteria in breast ultrasound.