  Tissue classification is one of the significant tasks in the field of
biomedical image analysis. Magnetic Resonance Imaging (MRI) is of great
importance in tissue classification especially in the areas of brain tissue
classification which is able to recognize anatomical areas of interest such as
surgical planning, monitoring therapy, clinical drug trials, image
registration, stereotactic neurosurgery, radiotherapy etc. The task of this
paper is to implement different unsupervised classification algorithms in ITK
and perform tissue classification (white matter, gray matter, cerebrospinal
fluid (CSF) and background of the human brain). For this purpose, 5 grayscale
head MRI scans are provided. In order of classifying brain tissues, three
algorithms are used. These are: Otsu thresholding, Bayesian classification and
Bayesian classification with Gaussian smoothing. The obtained classification
results are analyzed in the results and discussion section.
