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Identifying Patients at Risk for Aortic Stenosis Through Learning from Multimodal Data.

, , , , , , , and . MICCAI (3), volume 9902 of Lecture Notes in Computer Science, page 238-245. (2016)

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Identifying Patients at Risk for Aortic Stenosis Through Learning from Multimodal Data., , , , , , , and . MICCAI (3), volume 9902 of Lecture Notes in Computer Science, page 238-245. (2016)Image Synthesis with Aesthetics-Aware Generative Adversarial Network., , , and . PCM (2), volume 11165 of Lecture Notes in Computer Science, page 169-179. Springer, (2018)A novel method for tracking of muscle thickness changes in ultrasound image sequences., , , and . ICCH, page 72-74. IEEE, (2012)ε-Isometryε-Isometry based shape approximation for image content representation., , , and . Signal Process., 93 (8): 2293-2304 (2013)MR prostate segmentation via distributed discriminative dictionary (DDD) learning., , , , and . ISBI, page 868-871. IEEE, (2013)Segmenting Hippocampus from Infant Brains by Sparse Patch Matching with Deep-Learned Features., , , , , , and . MICCAI (2), volume 8674 of Lecture Notes in Computer Science, page 308-315. Springer, (2014)Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching., , and . Deep Learning for Medical Image Analysis, Academic Press, (2017)Intervertebral Disc Shape Analysis with Geodesic Metric in Shape Space., , , and . ICIG, page 320-324. IEEE Computer Society, (2011)Multi-class multimodal semantic segmentation with an improved 3D fully convolutional networks., and . Neurocomputing, (2020)A transversal approach for patch-based label fusion via matrix completion., , , , , and . Medical Image Anal., 24 (1): 135-148 (2015)