  The Positron Emission Tomography (PET) scan image requires expertise in the
segmentation where clustering algorithm plays an important role in the
automation process. The algorithm optimization is concluded based on the
performance, quality and number of clusters extracted. This paper is proposed
to study the commonly used K Means clustering algorithm and to discuss a brief
list of toolboxes for reproducing and extending works presented in medical
image analysis. This work is compiled using AForge .NET framework in windows
environment and MATrix LABoratory (MATLAB 7.0.1)
