This article deals with the evaluation of FPGAs resurgence for hardware acceleration applied to computed tomography on the back-projection operator used in iterative reconstruction algorithms. We focus our attention on the tools developed by FPGAs manufacturers, in particular the Intel FPGA SDK for OpenCL, that promises a new level of hardware abstraction from the developers perspective, allowing a software-like programming of FPGAs. Our first contribution is to propose an accurate memory benchmark, and we follow with an evaluation of different custom OpenCL implementations of the back- projection algorithm. With some clues on memory fetching and coalescing, we then further tune designs to improve performance. Finally, a comparison is made with GPU implementations, and a preliminary conclusion is drawn on FPGAs future for computed tomography.