Abstract
Real-time processing and visualization of 3D image data are the most important requirements for medical imaging. Among various 3D visualization methods, maximum intensity projection (MIP) is a useful tool to visualize 3D medical images. The processing time of the MIP depends on the number of voxels of the 3D data. Therefore, it is very difficult to realize the MIP of the 3D medical images in real time. In order to overcome the large computation amount of the MIP, we have developed a hierarchical MIP method that can perform the first-step MIP with average sub-sampled images, which is made from sub-sampled data by averaging. In the second step, the low-resolution MIP image and maximum sub-sampled voxels can be used to save the computation time of the full-resolution MIP image. The hierarchical MIP method was implemented, and its computation complexity and image quality were analyzed.
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