This paper presents an evolutionary algorithm for recognizing high and low crash road segments using Genetic Algorithm as a dynamic segmentation method. Social and economic costs as well as physical and mental injuries make the governments perceiving to road safety indexes in order to diminish the consequences of road accidents. Due to the limitation of budget for safety...

Introduction: Brain tumors such as glioma are among the most aggressive lesions, which result in a very short life expectancy in patients. Image segmentation is highly essential in medical image analysis with applications, particularly in clinical practices to treat brain tumors. Accurate segmentation of magnetic resonance data is crucial for diagnostic purposes, planning surgical treatments, a...

Due to the mass of sherds and vessels that have been dug out by archaeologists over many years, the request for an automatic classification system has become obvious. This paper presents algorithmic key ingredients of such a system: segmentation, feature extraction and clustering. Therefore, the extensive analysis of a representative profile line is of high importance, because it helps not only...

Segmentation of the left ventricle in echocardiographic images is a task with important diagnostic power. This paper describes a method for the calculation of the ventricle’s contours in longand short-axis views. The segmentation process starts with a complex border detection process, followed by the application of a generalized Hough transform to detect curves and ended up through an active-co...

‎This paper presents an application of partial differential equations(PDEs) for the segmentation of abdominal and thoracic aortic in CTA datasets. An important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been exte...

iris recognition is one of the most reliable methods for identification. in general, itconsists of image acquisition, iris segmentation, feature extraction and matching. among them, iris segmentation has an important role on the performance of any iris recognition system. eyes nonlinear movement, occlusion, and specular reflection are main challenges for any iris segmentation method. in this pa...

Spinal cord analysis is an important problem relating to the study of various neurological diseases. We present a novel approach to spinal cord segmentation in magnetic resonance images. Our method uses 3D "deformable organisms" (DefOrg) an artificial life framework for medical image analysis that complements classical deformable models (snakes and deformable meshes) with high-level, anatomical...

A brain tumor is a solid mass of abnormal cells within the brain.It is a set of some tissues that occur due to the rise of uncontrolled cell division. The work forms an image processing pipeline, consisting of noise reduction, feature extraction by image segmentation morphological operations to extract the region of interest. The work is based on the simultaneous use of two segmentation techniq...

The preoperative planning of primary tumor resections in the larynx region shall be supported by a 3D visualization of the patientspeci c anatomy and pathological situation. This requires a segmentation of the larynx cartilage structures from computed tomography (CT) datasets. In our work, we use 3D Stable Mass-Spring Models (SMSMs) for this segmentation task. Thereto, we create a speci c 3D de...

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...