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A combined deep-learning approach to fully automatic left ventricle segmentation in cardiac magnetic resonance imaging.

, , , , , , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 10953 of SPIE Proceedings, page 109531Y. SPIE, (2019)

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A combined deep-learning approach to fully automatic left ventricle segmentation in cardiac magnetic resonance imaging., , , , , , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 10953 of SPIE Proceedings, page 109531Y. SPIE, (2019)Cardiac motion estimation using pyramid, warping, and cost volume neural network., , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 11600 of SPIE Proceedings, SPIE, (2021)Siamese pyramidal deep learning network for strain estimation in 3D cardiac cine-MR., , , , , , and . Comput. Medical Imaging Graph., (September 2023)U-Net Neural Network for Locating Midpoint of Insertion Zone of Transcatheter Aortic Valves in CTA Images., , , , , , and . CinC, page 1-4. IEEE, (2021)Automatic myocardium strain quantification in MR synthetic images with Deep Leaning., , , , and . EMBC, page 545-548. IEEE, (2022)Improving the generalization of deep learning methods to segment the left ventricle in short axis MR images., , , , and . EMBC, page 1203-1206. IEEE, (2020)Topographic Identification of High-Risk Valvular Regions for Patients With Calcific Degenerative Aortic Valve Stenosis., , , , , , , , , and 2 other author(s). CinC, page 1-4. IEEE, (2019)