Artificial Intelligence in PET: an Industry Perspective

• URL: http://arxiv.org/abs/2107.06747v1
• Date: Wed, 14 Jul 2021 14:47:24 GMT
• Title: Artificial Intelligence in PET: an Industry Perspective
• Authors: Arkadiusz Sitek, Sangtae Ahn, Evren Asma, Adam Chandler, Alvin Ihsani, Sven Prevrhal, Arman Rahmim, Babak Saboury, Kris Thielemans
• Abstract summary: Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI poses industry-specific challenges which will need to be addressed and overcome to maximize the future potentials of AI in PET. This paper 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.
• Score: 3.084117449495927
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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 paper 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.

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