E
Eric K. Gibbons
Researcher at Stanford University
Publications - 7
Citations - 362
Eric K. Gibbons is an academic researcher from Stanford University. The author has contributed to research in topics: Imaging phantom & Signal-to-noise ratio (imaging). The author has an hindex of 4, co-authored 7 publications receiving 250 citations. Previous affiliations of Eric K. Gibbons include University of Utah.
Papers
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Journal ArticleDOI
Super-resolution musculoskeletal MRI using deep learning.
Akshay S. Chaudhari,Zhongnan Fang,Feliks Kogan,Jeffrey P. Wood,Kathryn J. Stevens,Eric K. Gibbons,Jin Hyung Lee,Garry E. Gold,Brian A. Hargreaves +8 more
TL;DR: To develop a super‐resolution technique using convolutional neural networks for generating thin‐slice knee MR images from thicker input slices, and compare this method with alternative through‐plane interpolation methods.
Journal ArticleDOI
Simultaneous NODDI and GFA parameter map generation from subsampled q-space imaging using deep learning.
Eric K. Gibbons,Kyler K. Hodgson,Akshay S. Chaudhari,Lorie Richards,Jennifer J. Majersik,Ganesh Adluru,Edward V. R. DiBella +6 more
TL;DR: To develop a robust multidimensional deep‐learning based method to simultaneously generate accurate neurite orientation dispersion and density imaging (NODDI) and generalized fractional anisotropy (GFA) parameter maps from undersampled q‐space datasets for use in stroke imaging.
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Utility of deep learning super-resolution in the context of osteoarthritis MRI biomarkers.
Akshay S. Chaudhari,Kathryn J. Stevens,Jeffrey P. Wood,Amit Chakraborty,Eric K. Gibbons,Zhongnan Fang,Arjun D. Desai,Jin Hyung Lee,Garry E. Gold,Brian A. Hargreaves +9 more
TL;DR: This work has shown that super‐resolution is an emerging method for enhancing MRI resolution and its impact on image quality is still unknown.
Journal ArticleDOI
Body Diffusion Weighted Imaging Using Non-CPMG Fast Spin Echo.
TL;DR: This method has the ability to capture distortion-free DWI images near areas of significant off-resonance as well as preserve adequate SNR and Parallel imaging and DIVERSE refocusing RF pulses allow shorter ETL compared to previous implementations and thus reduces phase encode direction blur and SAR accumulation.
Journal ArticleDOI
Body diffusion-weighted imaging using magnetization prepared single-shot fast spin echo and extended parallel imaging signal averaging.
TL;DR: A magnetization prepared diffusion‐weighted single‐shot fast spin echo (SS‐FSE) pulse sequence for the application of body imaging to improve robustness to geometric distortion and a scan averaging technique that is superior to magnitude averaging and is not subject to artifacts due to object phase is proposed.