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The Fourier reconstruction of a head section
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1974
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Computed TomographyImage ReconstructionEngineeringImage AnalysisFourier ReconstructionCt ScanSearch AlgorithmFourier ExpansionComputational AnatomyRadiologyHealth SciencesGeometric ModelingReconstruction TechniqueMedical ImagingModified Weighting FunctionFourier AnalysisNeuroimagingInverse ProblemsMedical Image ComputingBiomedical Imaging3D Imaging
Fourier reconstruction is a spatial-domain sum of line integrals weighted by distance from the line to the reconstruction point. The study proposes a modified weighting function to achieve accuracy, simplicity, low computation time, and low noise sensitivity. The authors use this weighting function to compare the Fourier algorithm with a search algorithm on a simulated phantom, then accelerate the search algorithm by reducing interactions, noting a trade‑off in resolution near the skull. The search algorithm required 12 iterations to match Fourier reconstruction accuracy and resolution but was more noise‑sensitive.
The Fourier reconstruction may be viewed simply in the spatial domain as the sum of each line integral times a weighting function of the distance from the line to the point of reconstruction. A modified weighting function simultaneously achieves accuracy, simplicity, low computation time, as well as low sensitivity to noise. Using a simulated phantom, the authors compare the Fourier algorithm and a search algorithm. The search algorithm required 12 iterations to obtain a reconstruction of accuracy and resolution comparable to that of the Fourier reconstruction, and was more sensitive to noise. To speed the search algorithm by using fewer interactions leaves decreased resolution in the region just inside the skull which could mask a subdural hematoma.