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The average temperature of Earth is the subject of much current discussion. Earth is in radiative contact with both the Sun and dark space; it receives almost all its energy from the radiation of the Sun and reflects some of it into outer space. Dark space is very cold, about 3 K, so Earth radiates energy into it. For instance, heat transfer occurs from soil and grasses, the rate of which can be so rapid that frost can occur on clear summer evenings, even in warm latitudes.
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Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
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Artificial Intelligence in Radiation Therapy.

Yabo Fu1, Hao Zhang2, Eric D Morris3

  • 1Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA.

IEEE Transactions on Radiation and Plasma Medical Sciences
|August 22, 2022
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) is revolutionizing radiotherapy by automating key tasks like image reconstruction and treatment planning. This review highlights AI

Keywords:
Artificial IntelligenceImage ReconstructionImage RegistrationImage SegmentationImage SynthesisRadiotherapyTreatment Planning

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Area of Science:

  • Radiotherapy and Medical Imaging

Background:

  • Artificial intelligence (AI) offers significant potential to enhance radiotherapy clinical workflows.
  • Deep neural networks have driven the development of numerous AI-based solutions for radiotherapy challenges.
  • Commercial AI tools are increasingly available for integration into clinical practice.

Purpose of the Study:

  • To review recent advancements in AI-aided radiotherapy.
  • To summarize and categorize AI-based methods across five key radiotherapy areas.
  • To discuss challenges, concerns, and future directions in AI-driven radiotherapy.

Main Methods:

  • Systematic review of AI-based studies in radiotherapy.
  • Categorization of AI methods in image reconstruction, registration, segmentation, synthesis, and treatment planning.
  • Analysis of challenges and future development in each category.

Main Results:

  • AI methods have been developed for image reconstruction, registration, segmentation, synthesis, and automatic treatment planning.
  • Commercial AI tools are emerging for clinical integration.
  • Significant progress has been made in applying AI to various radiotherapy tasks.

Conclusions:

  • AI-based approaches show promise for substantial improvements in radiotherapy efficiency and effectiveness.
  • Intelligent automation through AI can transform various aspects of the radiotherapy workflow.
  • Continued development in AI-aided radiotherapy is expected to enhance patient care.