In this paper, we present a new approach to the segmentation and analysis of solid breast nodules in ultrasonography. We have applied computer vision techniques to segment the nodules and analyze a series of diagnostic criteria, which can help discriminate malignant and benignant tumors. The segmentation is carried out by means of a combination of a region growing algorithm and the active contour technique. On the other hand, the analysis of the diagnostic criteria involves several methods, such as the extraction of the minimum distance ellipse through gradient descent, pseudocorner location or structure tensor. The methods that we propose have provided quite satisfactory results and show the usefulness of image processing techniques in the diagnosis by means of medical imaging. The aim of this work is not the substitution of the specialist, but the generation of a series of parameters which reduce the need of carrying out the biopsy. D
In this paper, we present a new approach to the segmentation and analysis of solid breast nodules in ultrasonography. We have applied computer vision techniques to segment the nodules and analyze a series of diagnostic criteria which can help discriminate malignant and benignant tumors. The segmentation is carried out in a semiautomatic way, whereas the analysis of the diagnostic criteria involves several computational methods. The techniques which we propose have provided quite satisfactory results and show the usefulness of image processing in the diagnosis through medical imaging.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.