This paper compares filtering methods for automated breast ultrasound images. The Perona-Malik diffusion filter, the diffusion stick filter and a simple median filter are evaluated as preprocessing methods for segmentation and characterization of lesions in breast ultrasound. In particular, preservation of small relevant image features, edge enhancement characteristics, and computational costs ...

Mammography is the most effective procedure for the early detection of breast cancer. The segmentation of mammograms plays a major role in isolating areas which can be subject to tumors. The identification of these zones is generally done in three stages: pectoral muscle segmentation, hard density zone detection and texture analysis of regions of interest. In this paper, a novel algorithm for d...

background: multiple sclerosis (ms) is a degenerative disease of central nervous system. ms patients have some dead tissues in their brains called ms lesions. mri is an imaging technique sensitive to soft tissues such as brain that shows ms lesions as hyper-intense or hypo-intense signals. since manual segmentation of these lesions is a laborious and time consuming task, automatic segmentation ...

This research describes a mammographic lesions using wavelet based active contour model. The sensitivity of the breast cancer detection was analyzed by mammography. Wavelet based decomposition techniques are used and tested for decomposing the noise present in the mammographic lesions. Gabor filtering method is used to reduce the unwanted noise obtained in the mammographic lesions by automated ...

Background: Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) provides functional information on the microcirculation in tissues by analyzing the enhancement kinetics which can be used as biomarkers for prostate lesions detection and characterization.Objective: The purpose of this study is to investigate spatiotemporal patterns of tumors by extracting semi-quantitative as well as w...

detecting blood vessels is an important task in retinal image analysis.  the task is more challenging with the presence of bright and dark lesions in retinal images. here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. first, the negative impact of bright lesions is reduced by using k-means segmentation in a perceptive sp...

Introduction: Accurate lesion segmentation is an important component of determining quantitative features for lesions on MRI. In this study, we develop an automated lesion segmentation method for delineating lesions on dynamic contrast enhanced (DCE)-MRI. We present a new active contour model which uses spectral embedding (SE), a process that partitions images in order to maximize intercluster ...

This paper presents a novel two-step approach that incorporates fuzzy c-means (FCMs) clustering and gradient vector flow (GVF) snake algorithm for lesions contour segmentation on breast magnetic resonance imaging (BMRI). Manual delineation of the lesions by expert MR radiologists was taken as a reference standard in evaluating the computerized segmentation approach. The proposed algorithm was a...

Mammograms are the soft X-rays meant for the detection of any lesions or cysts in breasts. Nowadays it is playing major role in the detection of breast cancer at an early stage. In this paper we have developed a computer aided diagnosis tool using MATLAB for breast cancer in Mamograms. This segmentation technique is based on the extraction of catchments basins through a topographic representati...

The computer-aided detection (CAD) systems have been developed to help radiologists with the early detection of breast cancer. This system provides objective and accurate information to reduce the misdiagnosis of the disease. In mammography, the pectoral muscle region is used as an index to compare the symmetry between the left and right images in the mediolateral oblique (MLO) view. The pector...