breast lesion segmentation in mr images is one of the most important parts of clinical diagnostic tools. pixel classification methods have been frequently used in image segmentation with two supervised and unsupervised approaches up to now. supervised segmentation methods lead to high accuracy, but they need a large amount of labeled data, which is hard, expensive, and slow to be obtained. on t...

texture image analysis is one of the most important working realms of image processing in medical sciences and industry. up to present, different approaches have been proposed for segmentation of texture images. in this paper, we offered unsupervised texture image segmentation based on markov random field (mrf) model. first, we used gabor filter with different parameters’ (frequency, orientatio...

assessment of cardiac right‑ventricle functions plays an essential role in diagnosis of arrhythmogenic right ventricular dysplasia (arvd). among clinical tests, cardiac magnetic resonance imaging (mri) is now becoming the most valid imaging technique to diagnose arvd. fatty infiltration of the right ventricular free wall can be visible on cardiac mri. finding right‑ventricle functional paramete...

Introduction Two-dimensional gel electrophoresis (2DGE) is a powerful technique in proteomics for protein separation. In this technique, spot segmentation is an essential stage, which can be challenging due to problems such as overlapping spots, streaks, artifacts and noise. Watershed transform is one of the common methods for image segmentation. Nevertheless, in 2DGE image segmentation, the no...

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 ...

The rapid development of electronic systems in automotive vehicles has been driven for decades by constantly growing requirements of legislation for environmental protection, as well as rising demands of the end-user to improve fuel economy, safety, driving comfort and driving excitement. The manufacturers of mobile work machines also see themselves increasingly confronted with these requiremen...

Recently, very deep networks, with as many as hundreds of layers, have shown great success in image classification tasks. One key component that has enabled such deep models is the use of “skip connections”, including either residual or highway connections, to alleviate the vanishing and exploding gradient problems. While these connections have been explored for speech, they have mainly been ex...

Usually, selection of a highway alignment depends on an economical route that minimizes alignment sensitive costs, such as construction cost, user cost, right-of-way cost, and earthwork cost. Most of the available highway alignment optimization algorithms do not consider traffic assignment and distribution of traffic as a result of the new road network consisting of the new alignment as well as...

this paper discusses the importance of environmental aesthetics and scenic beauty of currentroadside vegetation in the highways, and the necessity for the contribution of users (motorists) preferences inthe integration of scenic beauty of roadside vegetation into its management plans. the results of a questionnairesurvey of motorist’s opinion on the landscape aesthetics and quality of some high...

Highway construction has accelerated urban growth and induced direct and indirect changes to land use. Although many studies have analyzed the relationship between highway construction and local development, relatively less attention has been paid to clarifying the various impacts of highways associated with farmland loss. This paper integrates GIS spatial analysis, remote sensing, buffer analy...