1211 - Image-based deep-learning prediction of future FDG PET patterns in aging and dementia. (ID 532) - Society of Nuclear Medicine and Molecular Imaging 2019 Annual Meeting

1211 - Image-based deep-learning prediction of future FDG PET patterns in aging and dementia. (ID 532)

Physics, Instrumentation & Data Sciences -> Data Sciences 1211

1211 - Image-based deep-learning prediction of future FDG PET patterns in aging and dementia. (ID 532)

Session Name

Data Sciences Posters

Speakers

S. Komori

Authors

Presentation Topic

Physics, Instrumentation & Data Sciences -> Data Sciences

Presentation Number

1211

Previous Eposter

1200 - ⁶⁸Ga and ¹⁸F quantification, and detectability of hot spots using an ACR Phantom: Contributions of radionuclide physical differences to hot spot detectability (ID 474)

Next Eposters

1212 - Contribution of class activation map on WB PET deep features for primary tumour classification (ID 533)

1213 - A semi-automated method to separate tumor from physiological uptakes on FDG PET-CT for efficient generation of training data targeting deep learning (ID 534)

1215 - On the use of routine clinical MR images for synthetic CT generation in the head using a deep learning approach (ID 536)

1216 - An AI system using hybrid CNN and Radiomics model to improve PET image quality (ID 537)

1218 - Automated construction of patient-specific computational models using convolutional networks for conceptus dose estimation in pregnant patients (ID 539)

1220 - Usefulness of 18FDG-PET/CT in distinguishing HNF1A-mutated from inflammatory types of hepatocellular adenomas. (ID 540)

1227 - 4FMFES-PET in ER+ lobular breast cancer: revealing what FDG-PET could not (ID 746)

1231 - 99mTc nanocolloid indicyanine green: An hybrid tracer for breast sentinel node procedures (ID 748)

1232 - Relationship between tumor markers, Ca 15-3 and Ca 125, levels and Sodium-18 Fluoride Positron Emission Tomography Scan in breast cancer bone metastasis (ID 747)

1234 - Correlation between 18F-FDG PET/CT standardized uptake value with prognostic factors and gene expression profiles in breast cancer: Single center study from Azerbaijan (ID 752)