Interactive fusion and contrast enhancement for whole body PET/CT data using multi-image pixel composting

Abstract

The most important application of the dual-modality PET/CT is the ability to efficiently display the fused data. However, in PET/CT fusion, the amount of information displayed is often impaired as the CT data occupies greater range of contrast than that is possible to display without enhancements. A common approach to improving the CT information in the PET/CT fusion is by enhancing the contrast range of the CT data which can improve on the accuracy of structure localization and PET/CT interpretation. In this study, we present an interactive multi-image fusion which optimizes the display of the information from dual-modality PET/CT data. By interactively selecting a specific CT contrast range and assigning the resultant image as a layer, the multi-layers can be constructed and then fused using the multi-image pixel compositing. The enhanced CT data is further fused with the PET data for PET/CT diagnosis. The proposed algorithm is able to simultaneously display greater amount of information from the fused PET/CT data and reveal substantial details of the CT data that would not have been possible with standard PET/CT fusion. The preliminary results are encouraging and show potential in the PET/CT diagnosis and interpretation.