2024
Anatomically and Metabolically Informed Deep Learning Low-Count PET Image Denoising
Xia M, Xie H, Liu Q, Guo L, Ouyang J, Bayerlein R, Spencer B, Badawi R, Li Q, Fakhri G, Liu C. Anatomically and Metabolically Informed Deep Learning Low-Count PET Image Denoising. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10657099.Peer-Reviewed Original ResearchDeep learningOver-smoothed imagesDL training processesHigh-count imagesImage denoisingDenoised imageLow-count dataSemantic informationSemantic classesSegmentation guidanceTraining processPET/CT systemHistogram distributionImage qualitySegmentation toolPositron emission tomographyImagesDenoisingDatasetHistogramPriorsRadiation exposure2.5D Multi-view Averaging Diffusion Model for 3D Medical Image Translation: Application to Low-count PET Reconstruction with CT-less AC
Chen T, Hou J, Xie H, Chen X, Zhou Y, Xia M, Duncan J, Liu C, Zhou B. 2.5D Multi-view Averaging Diffusion Model for 3D Medical Image Translation: Application to Low-count PET Reconstruction with CT-less AC. 2024, 00: 1-2. DOI: 10.1109/nss/mic/rtsd57108.2024.10658551.Peer-Reviewed Original ResearchLow-dose PETStandard-dose PETImage-to-image translationPositron emission tomographyAttenuation correctionPET reconstructionOverall radiation doseCT acquisitionState-of-the-art deep learning methodsRadiation hazardRadiation doseCNN-based methodsState-of-the-artMedical image translationPatient studiesDiffusion modelDeep learning methodsHigh computation costHuman patient studiesClinical imaging toolImage translationBaseline methodsMulti-viewCNN-basedMultiple viewsTAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction
Guo X, Shi L, Chen X, Liu Q, Zhou B, Xie H, Liu Y, Palyo R, Miller E, Sinusas A, Staib L, Spottiswoode B, Liu C, Dvornek N. TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction. Medical Image Analysis 2024, 96: 103190. PMID: 38820677, PMCID: PMC11180595, DOI: 10.1016/j.media.2024.103190.Peer-Reviewed Original ResearchGenerative adversarial networkAdversarial networkMotion estimation accuracyInter-frame motionIntensity-based image registration techniqueAll-to-oneSegmentation masksImage registration techniquesOriginal frameTemporal informationDiagnosis accuracyMyocardial blood flowEstimation accuracyFrame conversionPositron emission tomographyNovel methodImage qualityPET datasetsRegistration techniqueNetworkCardiac positron emission tomographyBlood flowDynamic cardiac positron emission tomographyMotion correctionCoronary artery disease
2022
Inter-Pass Motion Correction for Whole-Body Dynamic PET and Parametric Imaging
Guo X, Wu J, Chen M, Liu Q, Onofrey J, Pucar D, Pang Y, Pigg D, Casey M, Dvornek N, Liu C. Inter-Pass Motion Correction for Whole-Body Dynamic PET and Parametric Imaging. IEEE Transactions On Radiation And Plasma Medical Sciences 2022, 7: 344-353. PMID: 37842204, PMCID: PMC10569406, DOI: 10.1109/trpms.2022.3227576.Peer-Reviewed Original ResearchPositron emission tomography
2021
Performance Evaluation of Amplitude and Phase Respiratory Gating Methods on Continuous-Bed-Motion Whole-Body PET Studies
Tsai Y, Lu Y, Wu J, Liu H, Schleyer P, Casey M, Liu C. Performance Evaluation of Amplitude and Phase Respiratory Gating Methods on Continuous-Bed-Motion Whole-Body PET Studies. IEEE Transactions On Radiation And Plasma Medical Sciences 2021, 6: 415-420. DOI: 10.1109/trpms.2021.3075383.Peer-Reviewed Original Research
2017
Investigation of Sub-Centimeter Lung Nodule Quantification for Low-Dose PET
Lu Y, Fontaine K, Germino M, Mulnix T, Casey M, Carson R, Liu C. Investigation of Sub-Centimeter Lung Nodule Quantification for Low-Dose PET. IEEE Transactions On Radiation And Plasma Medical Sciences 2017, 2: 41-50. DOI: 10.1109/trpms.2017.2778008.Peer-Reviewed Original ResearchMotion amplitudeLarge motion amplitudesVoxel sizeRespiratory motion correctionComprehensive simulationsReconstruction voxel sizeSimulationsMotion correctionPhantom studyFlight positron emission tomographyResolution recovery reconstructionMore accurate quantificationReconstruction algorithmAccurate quantificationHigh-resolution timeDifferent upsampling methodsUpsampling methodPositron emission tomographyAmplitudeSizeAdditional reduction
2014
WE‐G‐BRD‐06: Variation in Dynamic Positron Emission Tomography Imaging of Tumor Hypoxia in Early Stage Non‐Small Cell Lung Cancer Patients Undergoing Stereotactic Body Radiotherapy
Kelada O, Decker R, Zheng M, Huang Y, Xia Y, Gallezot J, Liu C, Rockwell S, Carson R, Oelfke U, Carlson D. WE‐G‐BRD‐06: Variation in Dynamic Positron Emission Tomography Imaging of Tumor Hypoxia in Early Stage Non‐Small Cell Lung Cancer Patients Undergoing Stereotactic Body Radiotherapy. Medical Physics 2014, 41: 520-520. DOI: 10.1118/1.4889490.Peer-Reviewed Original ResearchNon-small cell lung cancer patientsCell lung cancer patientsPositron emission tomographyTumor hypoxic volumeLung cancer patientsCancer patientsHypoxic volumeEarly stage non-small cell lung cancer patientsTumor hypoxiaTumor vascular responseStereotactic body radiotherapyTotal tumor volumeNovel pilot studyEmission Tomography ImagingPositron emission tomography (PET) imagingDifferent time pointsTreatment failureFirst patientVascular responsesBody radiotherapyNSCLC tumorsTreatment individualizationBlood ratioTumor volumeSingle patient