Methodology for fast interactive segmentation of the peritoneum and diaphragm in multi-modal 3D medical image
The segmentation of the peritoneum and diaphragm is important for the non-rigid registration and surgical simulation on the abdominal viscera region. However, there has been few works on the peritoneum or the abdominal viscera envelop segmentation. The challenge in segmentation of the peritoneum is caused by its complex shape and connection to the internal abdominal organs with similar intensity value, which limits the feasibility of the deformable segmentation methods. In this paper, we present two semi-automatic tools to perform a fast segmentation of a patient peritoneum and diaphragm based on the low curvature of the peritoneum along cranio-caudal direction. The segmentation of the peritoneum can be achieved by delineating several selected axial slices using 2D B-spline fitting technique, and the remaining slices can be segmented automatically with 3D B-spline interpolation technique. Experiments on the choice of the number of selected slice (NSS) for interactive segmentation are performed and demonstrated that 1015 slices are enough to reach an accurate segmentation and can be finished within several minutes. The segmentation of the diaphragm is performed in the sagittal view based on the segmentation result of the peritoneum and can be finished within several minutes also. The segmentation duration of these two interactive tools are also evaluated by six users, the experiment shows that they can finish the segmentation within 10min. The application of the peritoneum and diaphragm segmentation approach for abdominal visualization and registration is also shown. In conclusion, our developed tools for segmenting the peritoneum and diaphragm are efficient and fast and can play an important role for the surgical planning and simulation on the abdominal viscera. This approach can also inspire the segmentation of the other anatomy structures with low curvature.
abdominal viscera fast segmentation surgical planning non-rigid image registration peritoneum segmentation