Synthetic 18F-FDG PET Image Generation Using a Combination of Biomathematical Modeling and Machine Learning.

Abazari, Mohammad Amin; Soltani, Madjid; Moradi Kashkooli, Farshad; Raahemifar, Kaamran

Abazari, Mohammad Amin; Soltani, Madjid; Moradi Kashkooli, Farshad; Raahemifar, Kaamran.

Afiliação

Abazari MA; Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran.
Soltani M; Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran.
Moradi Kashkooli F; Faculty of Science, School of Optometry and Vision Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
Raahemifar K; Advanced Bioengineering Initiative Center, Multidisciplinary International Complex, K. N. Toosi Univesity of Technology, Tehran 14176-14411, Iran.

Cancers (Basel) ; 14(11)2022 Jun 03.

Article em En | MEDLINE | ID: mdl-35681767

Palavras-chave

[18F]-fluorodeoxyglucose positron emission tomography (18F-FDG PET) imaging; deep convolutional generative adversarial networks (DCGANs); kinetic modeling of diagnostic agents; medical image augmentation; multi-scale computational cancer modeling; spatiotemporal modeling; synthetic medical image generation; tumor-induced angiogenesis

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Irã

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