Enabling solutions for an efficient compression of PET-CT datasets

PET/CT oncological studies produce a huge amount of digital data, from several hundreds of Mbytes for static whole-body scans to the order of tens of Gbytes for gated whole-body studies. The need of efficient compression methods for these kind of image data comes up, both for archive and for transmission purpose, as, for example, for telemedicine applications, where bandwidth bottlenecks could make a data transmission service actually unusable. In this paper we propose and test an articulated coding system enabling the use of efficient compression of PET/CT multimodal datasets. In particular, we consider the opportunities coming from an exploitation of cross-modal information of PET-CT data, and we investigate methods for the reduction of computational complexity and memory usage. This lead to an increase of both reliability and coding efficiency.