Discussion
In this study, the 3D Res-UNet convolutional neural network (CNN) algorithm was trained for EC segmentation using enhanced VMICNN architectures are supervised models that are trained end to end to learn a hierarchy of features representing different levels of abstraction in a data-driven manner; therefore, good data determine a good model. There is a lack of soft tissue contrast on CT images, some of which are unsatisfactory. Although SDCT can provide both VMI and CI, the patients were scanned by conventional CT during daily work. In this research, we trained the CNN with same label on both VMIAccording to this research, the difference in the segmentation performance of DSC was statistically significant (