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
2023
Segmentation-Free PVC for Cardiac SPECT Using a Densely-Connected Multi-Dimensional Dynamic Network
Xie H, Liu Z, Shi L, Greco K, Chen X, Zhou B, Feher A, Stendahl J, Boutagy N, Kyriakides T, Wang G, Sinusas A, Liu C. Segmentation-Free PVC for Cardiac SPECT Using a Densely-Connected Multi-Dimensional Dynamic Network. IEEE Transactions On Medical Imaging 2023, 42: 1325-1336. PMID: 36459599, PMCID: PMC10204821, DOI: 10.1109/tmi.2022.3226604.Peer-Reviewed Original Research
2021
Shape-Regularized Unsupervised Left Ventricular Motion Network With Segmentation Capability In 3d+ Time Echocardiography
Ta K, Ahn SS, Stendahl JC, Sinusas AJ, Duncan JS. Shape-Regularized Unsupervised Left Ventricular Motion Network With Segmentation Capability In 3d+ Time Echocardiography. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2021, 00: 536-540. PMID: 34168721, PMCID: PMC8221369, DOI: 10.1109/isbi48211.2021.9433888.Peer-Reviewed Original ResearchConvolutional neural networkAccurate motion estimationCardiac motion patternsMotion estimation performanceDense displacement fieldB-mode echocardiography imagesSegmentation masksMedical imagesMotion estimationNeural networkSegmentation capabilityTarget imageUnsupervised estimationImportant taskSegmentationMotion patternsDisplacement fieldNetworkEchocardiography imagesEstimation performanceImagesLow signalAdditional challengesMotion networkNoise ratio
2020
Unsupervised motion tracking of left ventricle in echocardiography
Ahn SS, Ta K, Lu A, Stendahl JC, Sinusas AJ, Duncan JS. Unsupervised motion tracking of left ventricle in echocardiography. Proceedings Of SPIE--the International Society For Optical Engineering 2020, 11319: 113190z-113190z-7. PMID: 32994659, PMCID: PMC7521020, DOI: 10.1117/12.2549572.Peer-Reviewed Original ResearchMotion trackingGround truth displacement fieldsConvolutional neural networkAccurate motion trackingDense displacement fieldB-mode echocardiography imagesU-NetNeural networkTracking frameworkNon-rigid registration algorithmTarget imageRegistration algorithmTarget frameSource frameAlgorithmEchocardiography imagesFavorable performanceDatasetImagesTrackingDisplacement estimationLarge amountEchocardiographic imagesSegmentationNetwork
2017
Flow Network Based Cardiac Motion Tracking Leveraging Learned Feature Matching
Parajuli N, Lu A, Stendahl J, Zontak M, Boutagy N, Alkhalil I, Eberle M, Lin B, O’Donnell M, Sinusas A, Duncan J. Flow Network Based Cardiac Motion Tracking Leveraging Learned Feature Matching. Lecture Notes In Computer Science 2017, 10434: 279-286. DOI: 10.1007/978-3-319-66185-8_32.Peer-Reviewed Original ResearchCardiac motion trackingNeural networkMotion trackingTedious feature engineeringSiamese neural networkMotion tracking methodFeature engineeringSiamese networkFeature matchingGraph nodesImage patchesSpatiotemporal problemsTracking algorithmTracking methodEdge weightsNetworkLinear programmingConsistent constraintsAdditional important contributionTrackingAlgorithmDatasetProgrammingNodesMatching