To realize brain surgery simulation system or automatic diagnostic system of brain diseases which make use of cross-sectional images taken by MRI, it is necessary to extract and recognize principal tissues in the image automatically. There have been many researches about extraction of tissues, but previous methods have weak points : that is, the process of the extraction is slow and its result is rough. In order to overcome these drawbacks, we propose a new method which enables us to extract principal tissues automatically and fast by using knowledge. This method is based on binarization and classification of regions. At the classification process, we make use of an information on shapes of ventricles and relative locations between ventricles, which are given beforehand as knowledge. Our method uses T1 and T2 weighted images taken by Spin Echo method as original images and we extract white matter, gray matter, ventricles and celebrospinal fluid other than ventricles in these images.
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