78 citations · 302 across the 22 of their papers we have counts for
26 papers
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets
Frederic Wang, Han Qi, Alfredo De Goyeneche +3
Although deep learning (DL) methods are powerful for solving inverse problems, their reliance on high-quality training data is a major hurdle. This is significant in high-dimension…
Beat Pilot Tone (BPT): Simultaneous MR Imaging and RF Motion Sensing at Arbitrary Frequencies
Suma Anand, Michael Lustig
Purpose: To introduce a simple system exploitation with the potential to turn MRI scanners into general-purpose RF motion monitoring systems. Methods: Inspired by Pilot Tone (PT),…
High-fidelity Direct Contrast Synthesis from Magnetic Resonance Fingerprinting
Ke Wang, Mariya Doneva, Jakob Meineke +6
Magnetic Resonance Fingerprinting (MRF) is an efficient quantitative MRI technique that can extract important tissue and system parameters such as T1, T2, B0, and B1 from a single…
Rapid Fabrication of Low Impedance, 3D Dry Electrodes for Physiological Sensing
Ryan Kaveh, Natalie Tetreault, Karthik Gopalan +4
Medical electrophysiological sensors that can study the body and diagnose diseases depend on consistently low impedance electrode-skin interfaces. Clinical-standard wet electrodes…
Subtle Data Crimes: Naively training machine learning algorithms could lead to overly-optimistic results
Efrat Shimron, Jonathan I. Tamir, Ke Wang +1
While open databases are an important resource in the Deep Learning (DL) era, they are sometimes used "off-label": data published for one task are used for training algorithms for…
High Fidelity Deep Learning-based MRI Reconstruction with Instance-wise Discriminative Feature Matching Loss
Ke Wang, Jonathan I Tamir, Alfredo De Goyeneche +4
Purpose: To improve reconstruction fidelity of fine structures and textures in deep learning (DL) based reconstructions. Methods: A novel patch-based Unsupervised Feature Loss (UFL…