Unsupervised restoration of brain SPECT volumes

Thanks to its ability to yield functionally-based information, the three-dimensional (3D) SPECT imagery technique has become a great help in the diagnostic of cerebrovascular diseases. Nevertheless, due to the imaging process, the 3D SPECT images are blurred and consequently their interpretation by the clinician is often difficult. In order to improve the resolution of these images and then to facilitate their interpretation, we propose herein, to extend a recent image blind deconvolution technique (called the NAS-RIF technique) in order to improve both the spatial and the interslice resolution of SPECT volumes. This scheme requires a preliminary step in order to find the support of the object to be restored. In this paper, we propose to solve this problem thanks to an unsupervised 3D Markovian segmentation technique. This method has been successfully tested on numerous real and simulated brain SPECT volumes, yielding very promising restoration results1.