https://www.selleckchem.com/mTOR.html
Experimental results show that the estimated shape models given by our approach are clinically acceptable and significantly more accurate than that of the competing method.Skull segmentation from three-dimensional (3D) cone-beam computed tomography (CBCT) images is critical for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Convolutional neural network (CNN)-based methods are currently dominating volumetric image segmentation, but these methods suffer from the limited GPU memory and the large image
Like
Comment
Share
