Artificial Intelligence in PET: An Industry Perspective.

Journal: PET clinics
Published Date:

Abstract

Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI has the ability to enhance and optimize all aspects of the PET imaging chain from patient scheduling, patient setup, protocoling, data acquisition, detector signal processing, reconstruction, image processing, and interpretation. AI poses industry-specific challenges which will need to be addressed and overcome to maximize the future potentials of AI in PET. This article provides an overview of these industry-specific challenges for the development, standardization, commercialization, and clinical adoption of AI and explores the potential enhancements to PET imaging brought on by AI in the near future. In particular, the combination of on-demand image reconstruction, AI, and custom-designed data-processing workflows may open new possibilities for innovation which would positively impact the industry and ultimately patients.

Authors

  • Arkadiusz Sitek
  • Sangtae Ahn
    GE Research, 1 Research Circle KWC-1310C, Niskayuna, NY 12309, USA.
  • Evren Asma
  • Adam Chandler
    Global Scientific Collaborations Group, United Imaging Healthcare, America, 9230 Kirby Drive, Houston, TX 77054, USA.
  • Alvin Ihsani
    NVIDIA, 2 Technology Park Drive, Westford, MA 01886, USA.
  • Sven Prevrhal
    Philips Medical Systems Technologies Ltd., Advanced Technologies Center, Haifa, 3100202, Israel.
  • Arman Rahmim
  • Babak Saboury
    IBM Research, Almaden, San Jose, California.
  • Kris Thielemans
    Institute of Nuclear Medicine, University College London, UCL Hospital Tower 5, 235 Euston Road, London NW1 2BU, UK; Algorithms and Software Consulting Ltd, 10 Laneway, London SW15 5HX, UK.