Reducing the number of colors in an image while preserving its quality, is of importance in many applications such as image analysis and compression. It also decreases memory and transmission bandwidth requirements. Moreover, classification of image colors is applicable in image segmentation and object detection and separation, as well as producing pseudo-color images. In this paper, the Kohene...

Introduction: Lung cancer is one of the most common causes of cancer-related deaths worldwide. Nowadays PET/CT plays an essential role in radiotherapy planning specially for lung tumors as it provides anatomical and functional information simultaneously that is effective in accurate tumor delineation. The optimal segmentation method has not been introduced yet, however several ...

In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques. Major objective of this work is to detect cerebral atherosclerosis segmentation application. Detection some abnormal structures in body become difficult task complete with simple images. For expounding and distinguishing neural architecture brain an effective manner, ...

image segmentation is an important task in image processing and computer vision which attract many researchers attention. there are a couple of information sets pixels in an image: statistical and structural information which refer to the feature value of pixel data and local correlation of pixel data, respectively. markov random field (mrf) is a tool for modeling statistical and structural inf...

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...

Presently image segmentation remains the most crucial stage in processing system. The main idea ofimage is to partition or divide a random into several partitions depending on problem solve. In this paper, we will be presenting new method of skin cancer detection based Otsu’s thresholding algorithm and markercontrolled watershed method. This hybridization process first all started by segmenting...

In the present study, a hybrid semi-supervised pixel-based classification algorithm is proposed for the automatic segmentation of intracranial aneurysms in Computed Tomography Angiography images. The algorithm was designed to discriminate image pixels as belonging to one of the two classes: blood vessel and brain parenchyma. Its accuracy in vessel and aneurysm detection was compared with two ot...

This paper presents a technique for the segmentation of range images. It tends to be a hybrid approach that combines edge detection and region growing techniques toward accomplishing the task of segmentation. The surface coherency property of range data provided an important attribute, .;rhich enabled the improvision of extrinsic knowledge regarding the types of surface primitives existing with...