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Automatic Quality Assessment of Echocardiograms Using Convolutional Neural Networks: Feasibility on the Apical Four-Chamber View.

, , , , , , , , , , , and . IEEE Trans. Medical Imaging, 36 (6): 1221-1230 (2017)

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U-LanD: Uncertainty-Driven Video Landmark Detection., , , , , , , and . CoRR, (2021)Echo-SyncNet: Self-supervised Cardiac View Synchronization in Echocardiography., , , , , , and . CoRR, (2021)Cardiac point-of-care to cart-based ultrasound translation using constrained CycleGAN., , , , , , , , , and 4 other author(s). Int. J. Comput. Assist. Radiol. Surg., 15 (5): 877-886 (2020)Echocardiogram View Conversion using Clinically Constrained Conditional GAN., , , , and . ISBI, page 96-99. IEEE, (2021)An efficient deep landmark detection network for PLAX EF estimation using sparse annotations., , , , and . Medical Imaging: Image-Guided Procedures, volume 12034 of SPIE Proceedings, SPIE, (2022)A Unified Framework Integrating Recurrent Fully-Convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data., , , , , , , , , and 1 other author(s). DLMIA/ML-CDS@MICCAI, volume 11045 of Lecture Notes in Computer Science, page 29-37. Springer, (2018)Automatic Detection of Patients with a High Risk of Systolic Cardiac Failure in Echocardiography., , , , , , , , , and . DLMIA/ML-CDS@MICCAI, volume 11045 of Lecture Notes in Computer Science, page 65-73. Springer, (2018)Correction to Äutomatic Quality Assessment of Echocardiograms Using Convolutional Neural Networks: Feasibility on the Apical Four-Chamber View"., , , , , , , , , and 2 other author(s). IEEE Trans. Medical Imaging, 36 (9): 1992 (2017)U-LanD: Uncertainty-Driven Video Landmark Detection., , , , , , , and . IEEE Trans. Medical Imaging, 41 (4): 793-804 (2022)Quality Assessment of Echocardiographic Cine Using Recurrent Neural Networks: Feasibility on Five Standard View Planes., , , , , , , , and . MICCAI (3), volume 10435 of Lecture Notes in Computer Science, page 302-310. Springer, (2017)