Study of low-dose PET image recovery using supervised learning with CycleGAN

PET is a popular medical imaging modality for various clinical applications, including diagnosis and image-guided radiation therapy. The low-dose PET (LDPET) at a minimized radiation dosage is highly desirable in clinic since PET imaging involves ionizing radiation, and raises concerns about the ris...

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Veröffentlicht in:	PloS one 2020-09, Vol.15 (9), p.e0238455-e0238455
Hauptverfasser:	Zhao, Kui, Zhou, Long, Gao, Size, Wang, Xiaozhuang, Wang, Yaofa, Zhao, Xin, Wang, Huatao, Liu, Kanfeng, Zhu, Yunqi, Ye, Hongwei, Hatt, Mathieu
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Biology and Life Sciences Computer and Information Sciences Computer simulation Datasets Deep learning Diagnosis Dosage Drug dosages Engineering and Technology Evaluation Generative adversarial networks Generators Hospitals Image processing Image quality Ionizing radiation Machine learning Mapping Medical imaging Medical research Medical schools Medicine Medicine and Health Sciences Methods Neuroimaging Noise Positron emission Positron emission tomography Quality Radiation Radiation dosage Radiation effects Radiation therapy Radioactive tracers Recovery (Medical) Research and Analysis Methods Supervised learning Tomography
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