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
2004
Robust Filtering Strategies for Soft Tissue Young 'S Modulus Characterization
Shi P, Liu H, Sinusas A. Robust Filtering Strategies for Soft Tissue Young 'S Modulus Characterization. 2004, 2: 768-771. DOI: 10.1109/isbi.2004.1398651.Peer-Reviewed Original ResearchModulus characterizationContinuum mechanics modelTissue constitutive modelKalman filtering strategySoft tissue elasticityRobust filtering strategyConstitutive modelMaterial parametersMechanics modelFiltering strategyState-space representationTissue elasticityExperimental resultsKinematic stateSuperior performanceImage-derived measurementsLeast squares solutionFormulationUnifying formulationElasticity