Tianyi Zeng, PhD
Associate Research ScientistAbout
Research
Publications
2024
Performance Characteristics of the NeuroEXPLORER, a Next-Generation Human Brain PET/CT Imager
Li H, Badawi R, Cherry S, Fontaine K, He L, Henry S, Hillmer A, Hu L, Khattar N, Leung E, Li T, Li Y, Liu C, Liu P, Lu Z, Majewski S, Matuskey D, Morris E, Mulnix T, Omidvari N, Samanta S, Selfridge A, Sun X, Toyonaga T, Volpi T, Zeng T, Jones T, Qi J, Carson R. Performance Characteristics of the NeuroEXPLORER, a Next-Generation Human Brain PET/CT Imager. Journal Of Nuclear Medicine 2024, 65: jnumed.124.267767. PMID: 38871391, PMCID: PMC11294061, DOI: 10.2967/jnumed.124.267767.Peer-Reviewed Original ResearchPeak noise-equivalent count rateNoise-equivalent count rateTime-of-flight resolutionField of viewCount rateExtended axial field-of-viewTransverse field-of-viewAxial field-of-viewField-of-view centerMini-Derenzo phantomSpatial resolutionTangential spatial resolutionsCount rate performanceContrast recovery coefficientHuman brain PET imagingMeasurements of spatial resolutionNEMA sensitivityEnergy resolutionScatter fractionBrain phantomBackprojection reconstructionBrain PET imagingTime resolutionRadial offsetF-FDG imagingThe Software System of a Dedicated Brain PET Scanner Using Dual-Ended Readout Detectors With High DOI Resolution
Liu J, Ren N, Zeng T, Kuang Z, Zhang Q, Wang X, Liu Z, Zheng H, Liang D, Yang Y, Hu Z. The Software System of a Dedicated Brain PET Scanner Using Dual-Ended Readout Detectors With High DOI Resolution. IEEE Transactions on Radiation and Plasma Medical Sciences. 2024 Feb 26.Peer-Reviewed Original Research
2023
Markerless head motion tracking and event-by-event correction in brain PET
Zeng T, Lu Y, Jiang W, Zheng J, Zhang J, Gravel P, Wan Q, Fontaine K, Mulnix T, Jiang Y, Yang Z, Revilla E, Naganawa M, Toyonaga T, Henry S, Zhang X, Cao T, Hu L, Carson R. Markerless head motion tracking and event-by-event correction in brain PET. Physics In Medicine And Biology 2023, 68: 245019. PMID: 37983915, PMCID: PMC10713921, DOI: 10.1088/1361-6560/ad0e37.Peer-Reviewed Original ResearchConceptsPoint source studyHead motion correctionSmaller residual displacementMotion correctionIterative closest point (ICP) registration algorithmHead motion trackingSpatial resolutionResidual displacementData-driven evaluation methodHigh spatial resolutionLow noiseMotion trackingStereovision cameraMotion tracking deviceStructured lightEvent correctionBrain positron emission tomography (PET) imagingTracking deviceReconstruction resultsHMT methodPoint cloudsNegative biasReference cloudUMTEvaluation methodDevelopment and performance of SIAT bPET: a high-resolution and high-sensitivity MR-compatible brain PET scanner using dual-ended readout detectors.
Kuang Z, Sang Z, Ren N, Wang X, Zeng T, Wu S, Niu M, Cong L, Kinyanjui SM, Chen Q, Tie C, Liu Z, Sun T, Hu Z, Du J, Li Y, Liang D, Liu X, Zheng H, Yang Y. Development and performance of SIAT bPET: a high-resolution and high-sensitivity MR-compatible brain PET scanner using dual-ended readout detectors. Eur J Nucl Med Mol Imaging 2023 PMID: 37782321, DOI: 10.1007/s00259-023-06458-z.Peer-Reviewed Original ResearchFast Reconstruction for Deep Learning PET Head Motion Correction
Zeng T, Zhang J, Lieffrig E, Cai Z, Chen F, You C, Naganawa M, Lu Y, Onofrey J. Fast Reconstruction for Deep Learning PET Head Motion Correction. Lecture Notes In Computer Science 2023, 14229: 710-719. PMID: 38174207, PMCID: PMC10758999, DOI: 10.1007/978-3-031-43999-5_67.Peer-Reviewed Original ResearchCross-Attention for Improved Motion Correction in Brain PET
Cai Z, Zeng T, Lieffrig E, Zhang J, Chen F, Toyonaga T, You C, Xin J, Zheng N, Lu Y, Duncan J, Onofrey J. Cross-Attention for Improved Motion Correction in Brain PET. Lecture Notes In Computer Science 2023, 14312: 34-45. PMID: 38174216, PMCID: PMC10758996, DOI: 10.1007/978-3-031-44858-4_4.Peer-Reviewed Original ResearchDeep learning networkCross-attention mechanismDeep learning benchmarksMotion correctionTraining data domainPET list-mode dataPET image reconstructionQuality of reconstructionData domainCross attentionLearning networkSupervised mannerLearning benchmarksReference imageMotion trackingInherent informationList-mode dataImage reconstructionBrain PET dataPrediction resultsDifferent scannersHead motionImproved motion correctionNetworkSpatial correspondenceMulti-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction
Lieffrig E, Zeng T, Zhang J, Fontaine K, Fang X, Revilla E, Lu Y, Onofrey J. Multi-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2023, 00: 1-5. PMID: 38111738, PMCID: PMC10725741, DOI: 10.1109/isbi53787.2023.10230791.Peer-Reviewed Original ResearchMulti-task deep learningMulti-task architectureMonte Carlo dropoutTesting subjectsDeep learningMotion tracking deviceSupervised learningMotion correction methodNetwork predictionHead motion correctionAppearance predictionReconstructed imagesPrediction performanceImage acquisitionImage qualityTracking deviceMotion correctionLearning processUncertainty estimationTomography image acquisitionHead motionPrediction uncertaintyLearningQualitative resultsArchitectureFast Reconstruction for Deep Learning PET Head Motion Correction
Zeng, Tianyi, et al. "Fast Reconstruction for Deep Learning PET Head Motion Correction." International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland, 2023.Peer-Reviewed Original ResearchMulti-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction
Lieffrig, Eléonore V., et al. "Multi-Task Deep Learning and Uncertainty Estimation for Pet Head Motion Correction." 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). IEEE, 2023.Peer-Reviewed Original Research
2022
Supervised Deep Learning for Head Motion Correction in PET
Zeng T, Zhang J, Revilla E, Lieffrig E, Fang X, Lu Y, Onofrey J. Supervised Deep Learning for Head Motion Correction in PET. Lecture Notes In Computer Science 2022, 13434: 194-203. PMID: 38107622, PMCID: PMC10725740, DOI: 10.1007/978-3-031-16440-8_19.Peer-Reviewed Original ResearchDeep learning-based algorithmMotion tracking informationHead motion correctionNovel deep learningLearning-based algorithmMotion correctionDeep learningRegression layerEncoder layersTracking hardwareNetwork performanceSupervised mannerTracking informationAblation studiesRegistration approachCloud representationBrain positron emission tomography (PET) imagingTransformation layerDesign choicesReconstructed imagesPrediction performanceExternal devicesImage analysisTransformation parametersHead motion