Threshold-based Segmentation for 3D Medical Volumetric Images

This paper presented a threshold-based segmentation framework for 3D medical volumetric images,in which two classical image segmentation algorithms,OSTU and Gradient-based Segmentation,were re-designed and optimized to be suitable for 3D volumetric images.In order to evaluate the framework's performance,we defined two novel quantitative performance indicators:Segmentation Accuracy and Segmentation Balance,and use them to evaluate and analyze their performances.Experimental results show that both of the proposed segmentation algorithms can yield satisfied segmentation results for 3D medical volumetric images,and OSTU segmentation achieves better performance than Gradient-based segmentation.