Deep learning approach using SPECT-to-PET translation for attenuation correction in CT-less myocardial perfusion SPECT imaging.
Masateru KawakuboMichinobu NagaoYoko KaimotoRisako NakaoAtsushi YamamotoHiroshi KawasakiTakafumi IwaguchiYuka MatsuoKoichiro KanekoAkiko SakaiShuji SakaiPublished in: Annals of nuclear medicine (2023)
generation model may be applied as a low-cost and practical clinical tool that provides powerful auxiliary information for the diagnosis of myocardial blood flow.
Keyphrases
- blood flow
- low cost
- pet ct
- deep learning
- computed tomography
- positron emission tomography
- high resolution
- left ventricular
- dual energy
- image quality
- contrast enhanced
- machine learning
- artificial intelligence
- health information
- pet imaging
- magnetic resonance imaging
- convolutional neural network
- healthcare
- heart failure
- magnetic resonance
- fluorescence imaging