Experts provide a guided tour to PET image reconstruction for the application-oriented user. They share the pros and cons, and give you a glimpse of what to expect in the future with exciting insights into future trends.
Image reconstruction is a fundamental part of PET allowing to generate 3D tomographic images of the tracer’s spatial distribution based on the position and timing of the detected annihilation gammas. PET reconstruction, common to other imaging modalities like CT and SPECT, apply algorithms whose mathematical details the general users may not need to understand. Nevertheless, a good knowledge on the performance characteristics of different algorithms can be highly beneficial to obtain reliable quantitative images more efficiently.
In this Bruker webinar, Dr. Josep Oliver will provide an overview of all the basic concepts of PET image reconstruction. Josep will cover iterative and analytical algorithms discussing their fundamentals, as well as, their advantages and disadvantages and recommended settings. Key concepts like resolution, noise, artifacts and convergence will be explained in a manner that allows the application-oriented user to understand the impact of reconstruction parameters on quantification and image quality. Following, Dr. Harry Tsoumpas will discuss the importance of data corrections as part of image reconstruction and then will proceed with an outlook to exciting new PET image reconstruction opportunities arising from the availability of hybrid imaging devices combined with current trends in computer science.
Key Topics Include:
- Fundamentals of FBP and MLEM
- The importance of data corrections in image reconstruction
- Image reconstruction for quantification
- The role of MRI in improving PET images
- The potential of Artificial Intelligence in image reconstruction
Lecturer of Medical Imaging
University of Leeds
Senior NMI Image Reconstruction Expert