Image processing and analysis of PET and hybrid PET imaging

Abstract

PET imaging is a main diagnostic modality of different diseases including cancer. In the particular case of cancer, PET is widely used for staging of disease progression, identification of the treatment gross tumor volume, monitoring of disease, as well as prediction of outcomes and personalization of treatment regimens. Among the arsenal of different functional imaging modalities, PET has benefited from early adoption of quantitative image analysis starting from simple standard uptake value (SUV) normalization to more advanced extraction of complex imaging uptake patterns, thanks chiefly to the application of sophisticated image processing algorithms. In this chapter, we discuss the application of image processing techniques to PET imaging with special focus on the oncological radiotherapy domain starting from basic feature extraction to application in target definition using image segmentation/registration and more recent image-based outcome modeling in the radiomics field. We further extend the discussion into hybrid anatomical functional combinations of PET/CT and PET/MR multimodalities.