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Abstract #2555

Gridding: Exploring an Efficient Numerical Algorithm for 0-Th Order Prolate Spheroidal Wave Function Evaluation as Convolution Kernel

Laurent Lamalle1

1RMN biomdicale et Neurosciences SFR UJF, Inserm, Grenoble, Isre, France

An algorithm recently described for the efficient numerical evaluation of Prolate Spheroidal Wave Functions (PSWFs) was implemented in order to explore the possibility of using the 0-th order PSWF as convolution kernel in gridding reconstruction, instead of its Kaiser-Bessel approximation. The problem of evaluating the compensation function necessary after FFT of the samples interpolated by convolution with the kernel is addressed.