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Improving cardiac MRI convolutional neural network segmentation on small training datasets and dataset shift: A continuous kernel cut approach.

, , , , , , and . Medical Image Anal., (2020)

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Globally optimal co-segmentation of three-dimensional pulmonary 1H and hyperpolarized 3He MRI with spatial consistence prior., , , , , , , and . Medical Image Anal., 23 (1): 43-55 (2015)Fourier decomposition free-breathing H MRI perfusion maps in asthma., , , , , and . Medical Imaging: Image Processing, volume 10949 of SPIE Proceedings, page 1094912. SPIE, (2019)A Voxel-Based Fully Convolution Network and Continuous Max-Flow for Carotid Vessel-Wall-Volume Segmentation From 3D Ultrasound Images., , , , , , and . IEEE Trans. Medical Imaging, 39 (9): 2844-2855 (2020)Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study., , , , , , and . CoRR, (2020)Cardiac cine MRI left ventricle segmentation combining deep learning and graphical models., , and . Medical Imaging: Image Processing, volume 11313 of SPIE Proceedings, page 113130Z. SPIE, (2020)Improving cardiac MRI convolutional neural network segmentation on small training datasets and dataset shift: A continuous kernel cut approach., , , , , , and . Medical Image Anal., (2020)Cardiac MRI Left Ventricular Segmentation and Function Quantification Using Pre-trained Neural Networks., , , and . FIMH, volume 12738 of Lecture Notes in Computer Science, page 46-54. Springer, (2021)Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study., , , , , , and . IEEE Trans. Biomed. Eng., 70 (6): 1955-1966 (June 2023)Registration pipeline for pulmonary free-breathing 1H MRI ventilation measurements., , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 10137 of SPIE Proceedings, page 101370A. SPIE, (2017)Cine and Multicontrast Late Enhanced MRI Registration for 3D Heart Model Construction., , , , and . STACOM@MICCAI, volume 11395 of Lecture Notes in Computer Science, page 49-57. Springer, (2018)