Validation of Deep Learning-based Augmentation for Reduced 18F-FDG Dose for PET/MRI in Children and Young Adults with Lymphoma.
Ashok Joseph TheruvathFlorian SiedekKetan YerneniAnne M MueheSheri L SpuntAllison PribnowMichael E MoseleyYing LuQian ZhaoPraveen GulakaAkshay S ChaudhariHeike Elisabeth Daldrup-LinkPublished in: Radiology. Artificial intelligence (2021)
CNN enhancement of PET/MRI scans may enable 50% 18F-FDG dose reduction with correct treatment response assessment of children and young adults with lymphoma.Keywords: Pediatrics, PET/MRI, Computer Applications Detection/Diagnosis, Lymphoma, Tumor Response, Whole-Body Imaging, Technology AssessmentClinical trial registration no: NCT01542879 Supplemental material is available for this article. © RSNA, 2021.
Keyphrases
- pet ct
- positron emission tomography
- young adults
- contrast enhanced
- computed tomography
- pet imaging
- deep learning
- magnetic resonance imaging
- diffuse large b cell lymphoma
- diffusion weighted imaging
- convolutional neural network
- high resolution
- magnetic resonance
- clinical trial
- study protocol
- phase iii
- randomized controlled trial
- machine learning
- open label
- phase ii
- fluorescence imaging
- photodynamic therapy