In this paper we propose a new fuzzy segmentation method to segment lesions in Digital Breast Tomosynthesis (DBT) datasets. In the proposed approach we model a contour as a path in the image. The optimal contour is defined as the path associated with a minimal cost, which is derived from the image content. Using this formalism we present several ways to alter this cost in order to extract sever...

BACKGROUND This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. METHODS The image is divided into pixels subsets characterized by a set of conveniently chosen feat...

Background and Objectives:Breast cancer is the most common cancer among women worldwide. Fine needle aspiration biopsy (FNAB) is one of the methods of breast biopsy which is fast, easy and cost effective. The aim of this study was to evaluate the concordance rate between pathologic results of sonography or stereotaxy guided FNAB and guided core needle biopsy (CNB) in the evaluation of breast le...

In this research, a new method for automatic detection and classification of suspected breast cancer lesions using ultrasound images is proposed. In this fully automated method, de-noising using fuzzy logic and correlation among ultrasound images taken from different angles is used. Feature selection using combination of sequential backward search, sequential forward search and distance-based m...

Due to the low contrast, blurred boundary and intensity inhomogeneity of images, accurate segmentation breast cancer lesions with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) still has great challenges. This paper proposed an improved active contour model (ACM) for segmenting in DCE-MRI images. First, based on extreme learning machine (ELM) method, a robust function is that co...

This paper presents a methodology to study breast lesions captured from ultrasound (US) devices. One of the main problems behind this theme is the separation of the lesion from their background in order to further extract their features, allowing a better automatic analysis later. Previous works have shown that by considering such images as non-extensive physical systems allows implementation o...

Breast cancer is one of the leading causes death in México and among world. This mainly due to late diagnosis price treatment. Ultrasound (US) most used tools for image-based assessment this disease, since it can help discriminate solid vs. cystic masses, as well between benign or malignant masses. However, ultrasound imaging depends largely on radiologists experience. A detection not depending...

The focus of this paper is to review approaches for segmentation of breast regions in mammograms according to breast density. Studies based on density have been undertaken because of the relationship between breast cancer and density. Breast cancer usually occurs in the fibroglandular area of breast tissue, which appears bright on mammograms and is described as breast density. Most of the studi...

skin cancer has been the most usual and illustrates 50% of all new cancers detected each year. if they detected at an early stage, treatment can become simple and economically. accurate skin lesion segmentation is important in automated early skin cancer detection and diagnosis systems. the aim of this study is to provide an effective approach to detect the skin lesion border on a purposed imag...