Development of multi-detector row computed tomography (MDCT) has enabled three-dimensions (3D) scanning with minute voxels. Minute voxels improve spatial resolution of CT images. At the same time, however, they increase image noise. Multi-planar reconstruction (MPR) is one of effective 3D-image processing techniques. The conventional MPR technique can adjust slice thickness of MPR images. When a thick slice is used, the image noise is decreased. In this case, however, spatial resolution is deteriorated. In order to deal with this trade-off problem, we have developed the weighted-averaging multi-planar reconstruction (W-MPR) technique to control the balance between the spatial resolution and noise. The weighted-average is determined by the Gaussian-type weighting function. In this study, we compared the performance of W-MPR with that of conventional simple-addition-averaging MPR. As a result, we could confirm that W-MPR can decrease the image noise without significant deterioration of spatial resolution. W-MPR can adjust freely the weight for each slice by changing the shape of the weighting function. Therefore, W-MPR can allow us to select a proper balance of spatial resolution and noise and at the same time produce suitable MPR images for observation of targeted anatomical structures.
