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Tues-A17_01-Beatty-Gridding

于 2012-05-27 发布 文件大小:83KB
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  In this session, I will focus on the gridding method for fast image reconstruction from non- Cartesian data [1-5]. While gridding is not the only game in town, it is the reconstruction of choice when reconstruction time is an issue. Other reconstruction techniques include rBURS [6] and non-Cartesian iterative methods [7,8]. Non-Cartesian iterative methods generally use gridding and inverse gridding as their core operation, so even when gridding is not the right solution for an application, an understanding of gridding can be useful. I will cover the main steps of the gridding algorithm and then discuss some implementation tips that can signicantly reduce the computation time. Finally, I will present some illustrations and viewpoints that I have found to aid in an intuitive understanding of the gridding method, which can be helpful when designing the density compensation function and judging the appropriateness of gridding as a solution for a particular application.

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