2022
Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network
Guo X, Zhou B, Pigg D, Spottiswoode B, Casey ME, Liu C, Dvornek NC. Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network. Medical Image Analysis 2022, 80: 102524. PMID: 35797734, PMCID: PMC10923189, DOI: 10.1016/j.media.2022.102524.Peer-Reviewed Original ResearchMeSH KeywordsHumansImage Processing, Computer-AssistedMemory, Short-TermNeural Networks, ComputerPositron-Emission TomographyWhole Body ImagingConceptsConvolutional neural networkNeural networkConvolutional long short-term memory (ConvLSTM) layersDeep learning-based frameworkConvolutional long short-term memoryLong short-term memory layersDeep learning baselinesLong short-term memoryDynamic temporal featuresLearning-based frameworkDeep learning approachShort-term memory layersTracer distribution changeMotion estimation networkMotion prediction errorInference timeEstimation networkLearning baselinesNon-rigid registration methodLearning approachMotion correction methodMemory layerShort-term memoryTemporal featuresRegistration method
2021
Generation of parametric Ki images for FDG PET using two 5‐min scans
Wu J, Liu H, Ye Q, Gallezot J, Naganawa M, Miao T, Lu Y, Chen M, Esserman DA, Kyriakides TC, Carson RE, Liu C. Generation of parametric Ki images for FDG PET using two 5‐min scans. Medical Physics 2021, 48: 5219-5231. PMID: 34287939, DOI: 10.1002/mp.15113.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsFluorodeoxyglucose F18HumansPositron-Emission TomographyRadiopharmaceuticalsWhole Body ImagingConceptsPopulation-based input functionDynamic FDG-PET scansFDG-PET scansFDG-PETSUV changesPET scansClinical practiceSolid lung nodulesClinical usefulnessLate scansBone marrowRegion of interestLung nodulesInput functionScansPatlak analysisKi imagesMin/T-testCorrelation coefficientTumorsSubjectsNodulesDynamic imagingPET