[Weighted-averaging multi-planar reconstruction method for multi-detector row computed tomography]
Autor: | Mitsuhiro Aizawa, Mitsuru Yama, Keita Sasaki, Norio Kobayashi, Shinichi Murakami, Tsukasa Sano, Keiichi Nishikawa |
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Rok vydání: | 2012 |
Předmět: |
Computer science
business.industry Phantoms Imaging Resolution (electron density) Image processing General Medicine computer.software_genre Weighting Noise Imaging Three-Dimensional Voxel Multidetector Computed Tomography Image noise Image Processing Computer-Assisted Computer vision Tomography Artificial intelligence business Image resolution computer |
Zdroj: | Nihon Hoshasen Gijutsu Gakkai zasshi. 68(1) |
ISSN: | 1881-4883 |
Popis: | 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. |
Databáze: | OpenAIRE |
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