Luis Álvarez‐León scite author profile

International Congress Series

et al. 2005

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

show abstract

Computer Vision Techniques for Breast Tumor Ultrasound Analysis

et al. 2008

show abstract

Texture Classification through Multiscale Orientation Histogram Analysis

2003

Filtering, Segmentation and Feature Extraction in Ultrasound Evaluation of Breast Lesions

et al.

Abstract. The early diagnosis of breast cancer depends in many cases on the analysis of medical imaging, mainly mammography, ultrasonography and MRI. This work deals with ultrasound images in order to reduce speckle noise, identify the contour of the nodules and analyze a wide range of criteria which allow distinguishing between benign and malignant tumors. We try to automatize the different phases of the process and extract some objective parameters for a robust and reproducible diagnosis. We provide the physicians with both graphical as well as numerical results for the features which have been analyzed.

show abstract

Segmentation and Analysis of Breast Tumors on Ultrasonography

et al.