2024
Multi-Task Learning for Motion Analysis and Segmentation in 3D Echocardiography
Ta K, Ahn S, Thorn S, Stendahl J, Zhang X, Langdon J, Staib L, Sinusas A, Duncan J. Multi-Task Learning for Motion Analysis and Segmentation in 3D Echocardiography. IEEE Transactions On Medical Imaging 2024, 43: 2010-2020. PMID: 38231820, PMCID: PMC11514714, DOI: 10.1109/tmi.2024.3355383.Peer-Reviewed Original ResearchMulti-task learning networkCross-stitch unitsComposite loss functionAccurate motion estimationTask-specific networksMotion estimationSegmentation masksLearning networkLoss functionSegmentation stepEchocardiography datasetNetworkMotion displacementMotion analysisMultiple time framesTaskAnalysis pipelineSegmentsStrain measurementsDatasetRepresentation
2022
Co-attention spatial transformer network for unsupervised motion tracking and cardiac strain analysis in 3D echocardiography
Ahn S, Ta K, Thorn S, Onofrey J, Melvinsdottir I, Lee S, Langdon J, Sinusas A, Duncan J. Co-attention spatial transformer network for unsupervised motion tracking and cardiac strain analysis in 3D echocardiography. Medical Image Analysis 2022, 84: 102711. PMID: 36525845, PMCID: PMC9812938, DOI: 10.1016/j.media.2022.102711.Peer-Reviewed Original ResearchConceptsSpatial transformer networkMotion trackingNoisy displacement fieldReliable motion estimationMotion tracking methodCardiac strain analysisTransformer networkDisplacement fieldDisplacement pathsMotion fieldTracking methodMotion estimationExperimental resultsStrain analysisSuperior performanceTemporal constraintsCardiac motionTrackingRegularization functionDependent featuresEchocardiography imagesNetworkPrior assumptionsField
2008
INTEGRATED SEGMENTATION AND DEFORMATION ANALYSIS OF 4-D CARDIAC MR IMAGES
Zhu Y, Yan P, Papademetris X, Sinusas A, Duncan J. INTEGRATED SEGMENTATION AND DEFORMATION ANALYSIS OF 4-D CARDIAC MR IMAGES. 2008, 1437-1440. DOI: 10.1109/isbi.2008.4541277.Peer-Reviewed Original Research
2006
Sampled-Data ηα Filtering for Robust Kinematics Estimation: Applications to Biomechanics-Based Cardiac Image Analysis
Tong S, Sinusas A, Shi P. Sampled-Data ηα Filtering for Robust Kinematics Estimation: Applications to Biomechanics-Based Cardiac Image Analysis. 2014 IEEE International Conference On Image Processing (ICIP) 2006, 2525-2528. DOI: 10.1109/icip.2006.312955.Peer-Reviewed Original ResearchCanine MR phase contrast imagesPeriodic medical image sequencesContinuous-time state equationsDiscrete time instantsMore accurate estimation resultsAccurate estimation resultsCardiac image analysisKinematics estimationReal-world problemsMedical image sequencesState equationContinuous dynamicsParameter uncertaintiesSynthetic data experimentsModel uncertaintyState estimatesCardiac motion estimationTime instantsFiltering frameworkMotion estimationData disturbancesImage sequencesDiscrete measurementsNoisy natureData experiments
2001
The Active Elastic Model
Papademetris X, Constable R, Onat E, Duncan J, Sinusas A, Dione D. The Active Elastic Model. Lecture Notes In Computer Science 2001, 2082: 36-49. DOI: 10.1007/3-540-45729-1_4.Peer-Reviewed Original Research
1999
Volumetric Deformation Analysis Using Mechanics-Based Data Fusion: Applications in Cardiac Motion Recovery
Shi P, Sinusas A, Constable R, Duncan J. Volumetric Deformation Analysis Using Mechanics-Based Data Fusion: Applications in Cardiac Motion Recovery. International Journal Of Computer Vision 1999, 35: 87-107. DOI: 10.1023/a:1008163112590.Peer-Reviewed Original ResearchMotion estimationNon-rigid motion estimationInstantaneous velocity dataCardiac motion recoveryContinuum mechanics principlesMotion recovery problemData fusionImage sequencesVolumetric deformationPhysical objectsMechanics principlesDisplacement informationComplementary data sourcesDynamic behaviorMotion recoveryData sourcesVelocity dataRecovery problemMotion analysisNew methodDeformationEstimationMeaningful constraintsObjectsPatient diagnosis
1995
A Unified Framework to Assess Myocardial Function from 4D Images
Shi P, Robinson G, Chakraborty A, Staib L, Constable R, Sinusas A, Duncan J. A Unified Framework to Assess Myocardial Function from 4D Images. Lecture Notes In Computer Science 1995, 905: 327-337. DOI: 10.1007/978-3-540-49197-2_42.Peer-Reviewed Original ResearchA model-based integrated approach to track myocardial deformation using displacement and velocity constraints
Shi P, Robinson G, Constable R, Sinusas A, Duncan J. A model-based integrated approach to track myocardial deformation using displacement and velocity constraints. 1995, 687-692. DOI: 10.1109/iccv.1995.466872.Peer-Reviewed Original ResearchFinite element frameworkInstantaneous velocity informationVelocity informationElement frameworkMid-wall regionMotion trackingDeformationVelocity constraintsMotion estimationPhase-contrast magnetic resonance imagesAccurate estimationBiomechanical heart modelField motionBoundary informationNew methodBoundariesEstimationIntegrated approachDisplacementTracking