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Gregory J Metzger

Showing results (21-30 of 84) with videos related to

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Neuroimage|December 3, 2014
Theoretical and experimental evaluation of multi-band EPI for high-resolution whole brain pCASL ImagingXiufeng Li, Dingxin Wang, Edward J Auerbach, et al.
Magnetic Resonance in Medicine|September 14, 2023
Improved <sup>1</sup> H body imaging at 10.5 T: Validation and VOP-enabled imaging in vivo with a 16-channel transceiver dipole arraySimon Schmidt, M Arcan Ertürk, Xiaoxuan He, et al.
Magnetic Resonance in Medicine|January 26, 2021
Parallel transmit optimized 3D composite adiabatic spectral-spatial pulse for spectroscopyXiaoxuan He, Edward J Auerbach, Michael Garwood, et al.
AJR. American Journal of Roentgenology|April 14, 2021
Impact of 18-French Rectal Tube Placement on Image Quality of Multiparametric Prostate MRIYu-Hui Huang, Can Özütemiz, Nathan Rubin, et al.
Medical Physics|March 16, 2018
Development of a measure for evaluating lesion-wise performance of CAD algorithms in the context of mpMRI detection of prostate cancerEthan Leng, Benjamin Spilseth, Lin Zhang, et al.
Magnetic Resonance in Medicine|February 19, 2016
A 16-channel combined loop-dipole transceiver array for 7 Tesla body MRIM Arcan Ertürk, Alexander J E Raaijmakers, Gregor Adriany, et al.
IEEE Access : Practical Innovations, Open Solutions|September 16, 2021
Training Convolutional Networks for Prostate Segmentation With Limited DataSara L Saunders, Ethan Leng, Benjamin Spilseth, et al.
Medrxiv : the Preprint Server for Health Sciences|January 30, 2023
Improved Quantitative Parameter Estimation for Prostate T2 Relaxometry using Convolutional Neural NetworksPatrick J Bolan, Sara L Saunders, Kendrick Kay, et al.
Topics in Magnetic Resonance Imaging : TMRI|June 13, 2019
Evolution of UHF Body Imaging in the Human Torso at 7T: Technology, Applications, and Future DirectionsM Arcan Erturk, Xiufeng Li, Pierre-Fancois Van de Moortele, et al.
Magma (New York, N.Y.)|July 23, 2024
Improved quantitative parameter estimation for prostate T<sub>2</sub> relaxometry using convolutional neural networksPatrick J Bolan, Sara L Saunders, Kendrick Kay, et al.
Pageof 9

Showing results (21-30 of 84) with videos related to

Sort By:
Pageof 9
Neuroimage|December 3, 2014
Theoretical and experimental evaluation of multi-band EPI for high-resolution whole brain pCASL ImagingXiufeng Li, Dingxin Wang, Edward J Auerbach, et al.
Magnetic Resonance in Medicine|September 14, 2023
Improved <sup>1</sup> H body imaging at 10.5 T: Validation and VOP-enabled imaging in vivo with a 16-channel transceiver dipole arraySimon Schmidt, M Arcan Ertürk, Xiaoxuan He, et al.
Magnetic Resonance in Medicine|January 26, 2021
Parallel transmit optimized 3D composite adiabatic spectral-spatial pulse for spectroscopyXiaoxuan He, Edward J Auerbach, Michael Garwood, et al.
AJR. American Journal of Roentgenology|April 14, 2021
Impact of 18-French Rectal Tube Placement on Image Quality of Multiparametric Prostate MRIYu-Hui Huang, Can Özütemiz, Nathan Rubin, et al.
Medical Physics|March 16, 2018
Development of a measure for evaluating lesion-wise performance of CAD algorithms in the context of mpMRI detection of prostate cancerEthan Leng, Benjamin Spilseth, Lin Zhang, et al.
Magnetic Resonance in Medicine|February 19, 2016
A 16-channel combined loop-dipole transceiver array for 7 Tesla body MRIM Arcan Ertürk, Alexander J E Raaijmakers, Gregor Adriany, et al.
IEEE Access : Practical Innovations, Open Solutions|September 16, 2021
Training Convolutional Networks for Prostate Segmentation With Limited DataSara L Saunders, Ethan Leng, Benjamin Spilseth, et al.
Medrxiv : the Preprint Server for Health Sciences|January 30, 2023
Improved Quantitative Parameter Estimation for Prostate T2 Relaxometry using Convolutional Neural NetworksPatrick J Bolan, Sara L Saunders, Kendrick Kay, et al.
Topics in Magnetic Resonance Imaging : TMRI|June 13, 2019
Evolution of UHF Body Imaging in the Human Torso at 7T: Technology, Applications, and Future DirectionsM Arcan Erturk, Xiufeng Li, Pierre-Fancois Van de Moortele, et al.
Magma (New York, N.Y.)|July 23, 2024
Improved quantitative parameter estimation for prostate T<sub>2</sub> relaxometry using convolutional neural networksPatrick J Bolan, Sara L Saunders, Kendrick Kay, et al.
Pageof 9