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A comparative study of four popular 3-D image reconstruction algorithms has been made. Particular attention was given to artifacts generated and noise sensitivity. The methods considered include two spatial domain convolution algorithms, the Linear Superposition with Compensation (LSC) and a Fourier Convolution Method (FCM), a direct Fast Fourier Transform method (FFT), and an algebraic technique, the Simultaneous Iterative Reconstruction Technique (SIRT). The methods were compared by computing reconstructed images for an identical input phantom image. The phantom image contains several edges and a 2% contrast object. Variations, artifacts and noise sensitivity are easily visualized by perspective plots of the reconstructed images. Considerations as to the optimum algorithm for a particular application are discussed.