A fast maximum-intensity projection algorithm for generating magnetic resonance angiograms
S. Schreiner, Robert L. Galloway
Abstract
S. Schreiner, Robert L. Galloway
Abstract
Maximum-intensity projection (MIP) algorithms, a class of algorithms for construction of magnetic resonance (MR) angiograms, are reviewed. The blood flow in a volume of interest is represented by bright intensities in the MR data volume. MIP algorithms search for the maximum intensity along parallel rays cast through the MR image volume. A projection image is formed from these maximum intensity values. The flow within the vasculature shows up in the projection plane. An approach to calculating projections in which each image slice is presorted into bins of intensities is discussed. By relating the intensities of the pixels to their location in the slice, the total number of pixels considered for the projection plane is reduced, saving calculation time. Only the brighter intensities that relate to flow are used in the projection. Additional time savings result from precalculating projection templates and filling multiple projection planes at the same time. The algorithm was written in C on a 80386-based system. Results indicate a sixfold increase in projection calculation speed over a benchmark algorithm.
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Maximum-intensity projection (MIP) algorithms, a class of algorithms for construction of magnetic resonance (MR) angiograms, are reviewed. The blood flow in a volume of interest is represented by bright intensities in the MR data volume. MIP algorithms search for the maximum intensity along parallel rays cast through the MR image volume. A projection image is formed from these maximum intensity values. The flow within the vasculature shows up in the projection plane. An approach to calculating projections in which each image slice is presorted into bins of intensities is discussed. By relating the intensities of the pixels to their location in the slice, the total number of pixels considered for the projection plane is reduced, saving calculation time. Only the brighter intensities that relate to flow are used in the projection. Additional time savings result from precalculating projection templates and filling multiple projection planes at the same time. The algorithm was written in C on a 80386-based system. Results indicate a sixfold increase in projection calculation speed over a benchmark algorithm.
Key concepts: Maximum intensity projection, Projection (relational algebra), Projection plane, Pixel, Intensity (physics), Plane (geometry), Algorithm, Benchmark (surveying)