Unsupervised Method for 3D Brain Magnetic Resonance Image Segmentation

Abstract

Research at Digital Imaging and Communication in Medicine (DICOM) is very useful research in the field of health. In brain images, the problem encountered is when you want to divide or segment each part of the brain. In previous studies, some of research are still segmenting from 2-dimensional images, where the results will be different for each image slice. Therefore, in this research, we conducted the Magnetic Resonance Image (MRI) segmentation of the brain from the 3-dimensional plane to prevent the information contained in the images from being lost. In the early stages, MRI images will be converted to NifTi format to obtain 3-dimensional volume. The pre-processing is added as a modification from previous research, such as, convert image to grayscale, bias field correction, and skull stripping method to remove the skull (non-brain tissue) so that only brain tissue remains from the human brain. The segmentation process is done using multi-otsu thresholding. The experimental result shows that our method has successfully got three different brain tissue named white matter (WM), gray matter (GM), cerebrospinal fluid (CSF).