نتایج جستجو برای: means segmentation
تعداد نتایج: 412148 فیلتر نتایج به سال:
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...
In this paper, we study the ability of the cooperation of two-color pixel classification schemes (Bayesian and K-means classification) with color watershed. Using color pixel classification alone does not sufficiently accurately extract color regions so we suggest to use a strategy based on three steps: simplification, classification, and color watershed. Color watershed is based on a new aggre...
1. Texture segmentation can lead to multiscale outputs in which the partitions at successive scales are nested. 2. We can incorporate hierarchical segmentation into a K-Means clustering technique by steadily relaxing inter-cluster distances. 3. Thus, it is possible to hierarchically segment images based solely on texture measurements. 4. This hierarchical, multiscale segmentation is useful in i...
This paper presents a new method for automatic quantification of ellipse-like cells in images, an important and challenging problem that has been studied by the computer vision community. The proposed method can be described by two main steps. Initially, image segmentation based on the k-means algorithm is performed to separate different types of cells from the background. Then, a robust and ef...
Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering the importance of including spatial information of pixels which improves the quality of image segmentati...
Lung cancer is one of the most dangerous diseases that cause a large number of deaths. Early detection and analysis can be very helpful for successful treatment. Image segmentation plays a key role in the early detection and diagnosis of lung cancer. K-means algorithm and classic PSO clustering are the most common methods for segmentation that have poor outputs. In t...
like other sciences, market segmentation, as a science, seeks to realize unique needs of human being. in health market, individual diagnostic and curative methods are practiced more than anytime. however, a foundation of this market, pharmaceutical market, is not as advanced as other products and services markets in terms of segmentation. regarding the complexity of pharmaceutical market, it is...
Ray Casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a sufficiently powerful voxel parsing mechanism for object distinction. In this work, we are proposing an ...
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