Decision tree for 3-D connected components labeling

3-D connected components labeling is the fundamental technique in Magnetic Resonance Imaging (MRI). This research presents the decision tree for 3-D connected components labeling operation (26-connectivity) in 3-D binary images. This method will be used at the first round of the two-scan connected components labeling process. The distinctive characteristic of this method is its simplicity of the model by using the widely used fundamental algorithm which is the binary decision tree approach. This is very useful for developers to understand and implement the model rapidly. Moreover, this model can work correctly and rapidly with less time-consuming. It spends processing time just a little bit more than the fastest-processing model. Therefore, this method can be considered as one of the interesting techniques to perform 3-D connected components labeling algorithm.