An Optimization of System for Automatic Recognition of Ischemic Stroke Areas in Computed Tomography Images

Abstract. The paper considers application of stochastic optimization to system of automatic recognition of ischemic stroke area on computed tomography (CT) images. The algorithm of recognition depends on five inputs that influence the results of automatic detection. The quality of recognition is measured by size of conjunction of ethalone image and the image calculated by the program of automatic detection. The method of Simultaneous Perturbation Stohastic Approximation algorithm with the Metropolis rule has been applied to the optimization of the quality of image recognition. The Monte-Carlo simulation experiment was performed in order to evaluate the properties of developed algorithm. Key words: ischemic stroke area, Monte-Carlo method, computed tomography.

• Type: Journal
• Year: 2007
• Where: INFORMATICALT
• Authors: Darius Grigaitis, Vaida Bartkute, Leonidas Sakalauskas
• Keywords: Automatic Detection, Automatic Recognition, Image, INFORMATICALT 2007