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Emission computerized axial tomography is achievable in any nuclear medicine department from multiple gamma camera views. Data are collected by rotating the patient in front of the camera. A simple fast algorithm is implemented, known as the convolution technique: first the projection data are Fourier transformed and then an original filter designed for optimizing resolution and noise suppression is applied; finally the inverse transform of the latter operation is back-projected. This program, which can also take into account the attenuation for single photon events, was executed with good results on phantoms and patients. We think that it can be easily implemented for specific diagnostic problems.

The aim of our work is to realize the implementation of a real-time high-quality image rotation on FPGA's board. The method we used is based on M. Unser's work [1][2] and consists in applying a B-spline interpolator. The difficulty of this problem is due to the relatively weak integration capacity of FPGAs. To solve this problem, we have searched for determining the minimum number of bits to code the filter while keeping a good accuracy on filtering output. In this article, we remind a few definitions about B-spline functions and we present how we use B-spline interpolation for the image rotation problem. Then, we describe the way we calculate probability density function of the output error in order to determine the filter data coding.