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Brain hemorrhage detection and classification is a major help to physicians to rescue patients in an early stage. In this paper, we have tried to introduce an automatic detection and classification method to improve and accelerate the process of physicians' decision-making. To achieve this purpose, at first we have used a simple and effective segmentation method to detect and separate the hemorrhage...
This paper examines hybrid genetic algorithm and Gaussian Markov random field model based method for unsupervised segmentation of multi-spectral textured images. It also evaluates the popular unsupervised image segmentation approaches, Genetic algorithm (GA) based clustering and simple Gaussian Markov random field (GMRF) model with the hybrid GA-GMRF method for high spatial resolution textured imagery...
The development of power system video surveillance technology base on the development of image segmentation technology. Maximum variance between clusters (Otsu) is an complex, time-consuming image segmentation method. In light of this character, an optimization method. i. e. GA and PSO hybrid algorithm, which based the genetic algorithm (GA) and particle swarm optimization (PSO) is utilized to optimize...
So far, feather and down category recognition is often done by man with a microscope, but this method has some disadvantages. So a feather and down category recognition system is proposed in the paper, and then feather and down category recognition can be done by computer automatically. After the image processing and segmentation using GA, the triangle node of two-value image of feather and down is...
Currently, feather and down category recognition is often done by man with a microscope, but this method has some disadvantages. So a feather and down category recognition system is proposed in this paper, and feather and down category recognition is done by computer automatically. After the image processing and segmentation using GA, the triangle node of two-value image of feather is to be recognized...
Aiming at the characteristics of the marrow cell image, proposed a new method to calculate local regularity and got a appropriate threshold using multi-fractal spectrum so that accurate edges of different kinds of cells can be detected. Proposed a new genetic clustering algorithm based on entropy to classify the marrow cells. Through the experiences, better result can be attained.
This paper proposed a new segmentation algorithm of 3D medical image based on Hopfield neural networks. The method makes Hopfield neural networks and genetic algorithm (GA) combined and use texture analysis to achieve segmentation of tumor CT image. This method not only overcome shortcoming that the Hopfield neural network easily converge to local optimal solution, but also break the constraints that...
We present a novel approach for image segmentation using genetic algorithm (GA) implemented in cellular neural networks (CNNUM). This paper also demonstrates how the cellular neural universal machine architecture can be extended to image segmentation. It uses the highly parallel nature of the CNN structure and its speed outperforms traditional digital computers. The GA starts with a population of...
In this paper we present a segmentation method based on genetic active contours (genetic snakes) that are active contour models, also known as snakes, with an energy minimization procedure based on genetic algorithms (GA). Genetic snakes have been proposed to overcome some limits of the classical snakes, as initialization and existence of multiple minima, and have been successfully applied to images...
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