The echo-dephased SSFP technique could successfully visualise SPIO-labelled human and rat pancreatic islets yielding a positive contrast.

Image reconstruction is an essential part of the magnetic resonance imaging process, and a whole field of research is dedicated to the development of reconstruction algorithms. For this reason, scanner manufacturers provide researchers with programming frameworks that give full control over the whole procedure. The drawback is that these environments are complex, and the code is non-portable and covered by non-disclosure agreements. In this article, a simplified framework based on a free scripting language (Lua) is presented. It is oriented to the development of postprocessing algorithms that are seamlessly integrated with the pipeline of a commercial scanner. The structure privileges simplicity over performance, to be quickly learned and used by researchers and students who might not be acquainted with low-level programming languages. Common postprocessing algorithms (contrast modulation, pixelwise fitting, phase-contrast imaging) could be implemented with 100 logical lines of code or less, using a syntax that is similar to the Matlab programming language. The average performance of the reconstruction was lower with respect to the native implementation, but superior to offline postprocessing on a desktop computer, without the bottleneck of offline data export.