Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
80 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
7 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Artificial Intelligence in PET: an Industry Perspective (2107.06747v1)

Published 14 Jul 2021 in cs.CV and cs.AI

Abstract: 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.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (9)
  1. Arkadiusz Sitek (25 papers)
  2. Sangtae Ahn (8 papers)
  3. Evren Asma (2 papers)
  4. Adam Chandler (1 paper)
  5. Alvin Ihsani (7 papers)
  6. Sven Prevrhal (2 papers)
  7. Arman Rahmim (54 papers)
  8. Babak Saboury (12 papers)
  9. Kris Thielemans (12 papers)
Citations (4)