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 methodCross-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 correspondence