Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning
Shi L, Lu Y, Dvornek N, Weyman CA, Miller EJ, Sinusas AJ, Liu C. Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning. IEEE Transactions On Medical Imaging 2021, 40: 3293-3304. PMID: 34018932, PMCID: PMC8670362, DOI: 10.1109/tmi.2021.3082578.Peer-Reviewed Original ResearchConceptsConvolutional neural networkRegistration-based methodMotion correctionDynamic frameTracer distribution changeDynamic image dataPatient motion correctionPatient scansDeep learningPatient motionMotion estimationImage dataLSTM networkNeural networkRealistic patient motionTemporal informationMotion correction methodMotion detectionCardiac PETClinical workflowRigid translational motionFlow estimationNetworkPatient datasetsSuperior performanceDiagnostic accuracy of stress-only myocardial perfusion SPECT improved by deep learning
Liu H, Wu J, Miller EJ, Liu C, Yaqiang, Liu, Liu YH. Diagnostic accuracy of stress-only myocardial perfusion SPECT improved by deep learning. European Journal Of Nuclear Medicine And Molecular Imaging 2021, 48: 2793-2800. PMID: 33511425, DOI: 10.1007/s00259-021-05202-9.Peer-Reviewed Original ResearchConceptsMyocardial perfusion imagingCoronary artery diseaseMyocardial perfusion abnormalitiesPerfusion abnormalitiesDiagnostic accuracyConvolutional neural networkTomography myocardial perfusion imagingYale-New Haven HospitalMyocardial perfusion defect sizeSPECT myocardial perfusion imagingAbnormal myocardial perfusionReceiver-operating characteristic curvePerfusion defect sizeNew Haven HospitalAUC valuesSingle photon emissionMyocardial perfusion SPECTDeep learningHigh diagnostic accuracyArtery diseaseDL methodsFinal diagnosisPatient genderMyocardial perfusionPerfusion SPECT