Adaptive 3D image segmentation based on optimized PCNN

The segmentation algorithm with PCNN model has many natural advantages.But the typical PCNN model has too many parameters difficult to determinate and consumes too much time.This paper proposed an effective three dimension image segmentation model that integrated multiple PCNN models and the statistical model.It was used to segment brain MRI image into gray matter(GM),white matter(WM) and cerebrospinal fluid(CSF).And the segmentation results were compared with those of standard PCNN,traditional Otsu threshold,SPM8 toolbox and expert segmentation.It demonstrates this adaptive method is fairly accurate and effective.