IDENTIFIKASI CITRA OTAK MRI BERBASIS LOGIKA FUZZY TEROPTIMASI DAN EIGENBRAIN IMAGE - , INDAH SOESANTI, S.T., M.T. ([Yogyakarta] : Universitas Gadjah Mada, 2011)
Medical modern devices in imaging have supported medical patient diagnosis. The important medical information could not naturally visible. The statements about what, where, and how much the medical information intensity, can be achieved by using the appropriate image processing procedures. One of the potential procedures is the unsupervised segmentation method based on optimized fuzzy logic. This is the Fuzzy C-Means (FCM) clustering. In the first step, the appropriate adaptive segmentation for the MRI brain images based on modified FCM clustering with the spatial information was introduced. The results indicated that the noise problems have been handled sufficiently. After the segmentation step was achieved, then, the special feature extraction based on the eigenbrain image was done. In the final step, the nearest distance eigenbrain between reference image and test image was used to identify the segmented images from the medical field point of view. The results of MRI brain image identification conformed 100% with the medical diagnosis, for reduced image sizes from 256x256 to 64x64 pixels.