| 摘要 |
An automatic segmentation method for a cervical cancer image based on T2-weighted magnetic resonance imaging (T2-MRI) and diffusion-weighted magnetic resonance imaging (DW-MRI), including: registering a DW-MR image to a T2-MR image using a nonlinear registration method, and classifying the registered DW-MR image; filtering the T2-MR image using a nonlinear anisotropic diffusion filtering technique, segmenting a bladder and a rectum, and segmenting a region of interest using the segmentation results of the bladder and the rectum; and performing accurate segmentation of a tumour on the region of interest of the T2-MR image and the DW-MR image using a combined maximum a posteriori probability (CMAP) method. The present invention makes full use of the effective information about a T2-MR image and a DW-MR image, can effectively overcome the influences of noise, partial volume effect and intensity overlap in the T2-MR image, is an accurate and effective segmentation method for cervical cancer, and has important clinical significance and application value for the prevention, diagnosis and treatment of cervical cancer. |
