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Improving multi-atlas cardiac structure segmentation of computed tomography angiography: A performance evaluation based on a heterogeneous dataset.

, , , , , , and . Comput. Biol. Medicine, (2020)

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DeepHeartCT: A fully automatic artificial intelligence hybrid framework based on convolutional neural network and multi-atlas segmentation for multi-structure cardiac computed tomography angiography image segmentation., , , , , , , , and . Frontiers Artif. Intell., (2022)Quantitative CT Metrics Associated with Variability in the Diffusion Capacity of the Lung of Post-COVID-19 Patients with Minimal Residual Lung Lesions., , , , , , , , , and . J. Imaging, 9 (8): 150 (2023)An automatic random walk based method for 3D segmentation of the heart in cardiac computed tomography images., , , and . ISBI, page 1352-1355. IEEE, (2018)Comparison of lossless video and image compression codecs for medical computed tomography datasets., , , , and . IEEE BigData, page 3960-3962. IEEE Computer Society, (2016)Improving multi-atlas cardiac structure segmentation of computed tomography angiography: A performance evaluation based on a heterogeneous dataset., , , , , , and . Comput. Biol. Medicine, (2020)Simultaneous Multi-Structure Segmentation of the Heart and Peripheral Tissues in Contrast Enhanced Cardiac Computed Tomography Angiography., , , , , , , and . IEEE Access, (2020)Automatic estimation of aortic and mitral valve displacements in dynamic CTA with 4D graph-cuts., , , , , , and . Medical Image Anal., (2020)Accurate, fully-automated registration of coronary arteries for volumetric CT digital subtraction angiography., , , , , , , and . Medical Imaging: Image Processing, volume 9034 of SPIE Proceedings, page 90343F. SPIE, (2014)