Normal model construction for statistical image analysis of torso FDG-PET images based on anatomical standardization by CT images from FDG-PET/CT devices.
Kenshiro TakedaTakeshi HaraXiangrong ZhouTetsuro KatafuchiMasaya KatoSatoshi ItoKeiichi IshiharaShinichiro KumitaHiroshi FujitaPublished in: International journal of computer assisted radiology and surgery (2017)
The results suggested the possibility of applying a quantitative image reading method for torso FDG-PET imaging. Furthermore, a combination of the SUV and Z-score may provide increased accuracy of the determination methods, such as computer-aided detection and diagnosis.
Keyphrases
- pet imaging
- deep learning
- positron emission tomography
- convolutional neural network
- computed tomography
- optical coherence tomography
- image quality
- dual energy
- high resolution
- working memory
- machine learning
- pet ct
- solid phase extraction
- contrast enhanced
- real time pcr
- magnetic resonance imaging
- molecularly imprinted
- label free