6 citations · 22 across the 8 of their papers we have counts for
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physics.med-ph2021★ 2 cited
Quantitative Parametric Mapping of Tissues Properties from Standard Magnetic Resonance Imaging Enabled by Deep Learning
Yan Wu, Yajun Ma, Youngwook Kee +10
Magnetic resonance imaging (MRI) offers superior soft tissue contrast and is widely used in biomedicine. However, conventional MRI is not quantitative, which presents a bottleneck…
cs.LG2021★ 3 cited
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
Arda Sahiner, Tolga Ergen, Batu Ozturkler +4
Generative Adversarial Networks (GANs) are commonly used for modeling complex distributions of data. Both the generators and discriminators of GANs are often modeled by neural netw…
cs.CV2021★ 1 cited
A Geometry-Informed Deep Learning Framework for Ultra-Sparse 3D Tomographic Image Reconstruction
Liyue Shen, Wei Zhao, Dante Capaldi +2
Deep learning affords enormous opportunities to augment the armamentarium of biomedical imaging, albeit its design and implementation have potential flaws. Fundamentally, most deep…