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Abstract
No one knows what the paradigm shift of artificial intelligence will bring to medical imaging. In this article, we attempt to predict how artificial intelligence will impact radiology based on a critical review of current innovations. The best way to predict the future is to anticipate, prepare, and create it. We anticipate that radiology will need to enhance current infrastructure, collaborate with others, learn the challenges and pitfalls of the technology, and maintain a healthy skepticism about artificial intelligence while embracing its potential to allow us to become more productive, accurate, secure, and impactful in the care of our patients.
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Affiliation(s)
- Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10 Room 1C455, Bethesda, MD 20892, USA; Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, 1000 Hilltop Cir, Baltimore, MD 21250, USA; Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Michael Morris
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Building 10 Room 1C455, Bethesda, MD 20892, USA; Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, 1000 Hilltop Cir, Baltimore, MD 21250, USA; Division of Clinical Informatics, Networking Health, 331 Oak Manor Drive STE 201, Glen Burnie, MD 21061, USA
| | - Eliot Siegel
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 South Greene Street, Baltimore, MD 20201, USA; Department of Diagnostic Imaging, VA Maryland Healthcare System, 10 North Greene Street, Baltimore, MD 21201, USA.
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Sitek A, Ahn S, Asma E, Chandler A, Ihsani A, Prevrhal S, Rahmim A, Saboury B, Thielemans K. Artificial Intelligence in PET: An Industry Perspective. PET Clin 2021; 16:483-492. [PMID: 34353746 DOI: 10.1016/j.cpet.2021.06.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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.
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Affiliation(s)
- Arkadiusz Sitek
- Sano Centre for Computational Medicine, Nawojki 11 Street, Kraków 30-072, Poland.
| | - Sangtae Ahn
- GE Research, 1 Research Circle KWC-1310C, Niskayuna, NY 12309, USA
| | - Evren Asma
- Canon Medical Research, 706 N Deerpath Drive, Vernon Hills, IL 60061, USA
| | - 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 Research Europe, Röntgenstr. 22, Hamburg 22335, Germany
| | - Arman Rahmim
- Department of Radiology, University of British Columbia, BC Cancer, BC Cancer Research Institute, 675 West 10th Avenue, Office 6-112, Vancouver, British Columbia V5Z 1L3, Canada; Department of Physics, University of British Columbia, BC Cancer, BC Cancer Research Institute, 675 West 10th Avenue, Office 6-112, Vancouver, British Columbia V5Z 1L3, Canada
| | - Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA; Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, USA; Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - 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
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