Fast 3D reconstruction from medical image series based on thresholding method Eşikleme metodunu kullanarak medikal görüntü serisinden hizli 3 boyutlu model oluşturma

Many practical applications in the field of medical image processing need valid, reliable and fast image segmentation. In this study, we propose a semi-automatic segmentation approach. In this approach, an extended version of the Otsu's method for three level thresholding and a recursive connected component algorithm are combined. The segmentation process is accomplished using Extended Otsu's method and labeling in each consecutive slice. Extended Otsu's method is a thresholding method selecting two threshold values that maximizes the between-class variances, essentially by this way within-class variances are also minimized. Since information on pixel positions does not affect the outcome of Extended Otsu's method, we need to perform some processing after labeling. This processing comprises area filtering and searching the regions of interest. The proposed approach is applied to the consecutive slices. For this reason, the 3D segmentation is successfully achieved from 2D medical images. The approach not only is efficient and reliable but also requires very limited user intervention.