Performance of a deep learning enhancement method applied to PET images acquired with a reduced acquisition time.
Krzysztof CiborowskiAnna Gramek-JedwabnaMonika GołąbIzabela MiechowiczJolanta SzczurekMarek A RuchałaRafał CzepczyńskiPublished in: Nuclear medicine review. Central & Eastern Europe (2023)
The studied deep learning enhancement method can be used to accelerate PET acquisitions without compromising quantitative SUVmax values. AI-based algorithms can enhance the image quality of accelerated PET acquisitions, enabling the dose reduction to the patients and improving the cost-effectiveness of PET/CT imaging.
Keyphrases
- pet ct
- deep learning
- positron emission tomography
- artificial intelligence
- image quality
- computed tomography
- convolutional neural network
- machine learning
- end stage renal disease
- high resolution
- newly diagnosed
- ejection fraction
- chronic kidney disease
- prognostic factors
- patient reported outcomes
- magnetic resonance
- dual energy
- photodynamic therapy
- fluorescence imaging