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Today, information obtained a medical image is important for a diagnosis. Especially, ultrasonic image has the merits of the simplicity of the machine, low cost, and safety. On the other hand, ultrasonic image is sometimes poor in quality because of much noise. Therefore, the diagnosis by ultrasonic image has been depended on the judgement of skilled doctors. It is necessary to develope a method of an automatic diagnosis that is based on a qualitative evaluation. In order to extract automatically a region of an internal organs or a region of focus from medical ultrasonic image, it is neccesary to detect a defferrence of some quantitative features between a region as a purpose and other regions. Usual methods for regional extraction of ultrasonic image was based on features defined from gray-level or statistical characters of speckle pattern. In those methods, various features were defined as applying texture analysis. But effective feature, that is used to extract a tissue region as a purpose, is seleceted empirically. In this research, we propose a mothod to select an optimal set of discriminating functions, that is composed of effective features to extract tissue region by use of genetic algorithm (GA).

A Methodology for Selection of Optimal Discriminating Function to Extract Tissue Region from Medical Ultrasonic Image