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Daniel K. Sodickson
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2020 – today
- 2024
- [j6]Radhika Tibrewala
, Douglas Brantner, Ryan Brown
Preliminary Experience with Three Alternative Motion Sensors for 0.55 Tesla MR Imaging. Sensors 24(12): 3710 (2024) - 2023
- [c9]Divyam Madaan, Daniel K. Sodickson, Kyunghyun Cho, Sumit Chopra:
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis. MIDL 2023: 1726-1750 - [i10]Raghav Singhal, Mukund Sudarshan, Anish Mahishi, Sri Kaushik, Luke Ginocchio, Angela Tong, Hersh Chandarana, Daniel K. Sodickson, Rajesh Ranganath, Sumit Chopra:
On the Feasibility of Machine Learning Augmented Magnetic Resonance for Point-of-Care Identification of Disease. CoRR abs/2301.11962 (2023) - [i9]Radhika Tibrewala, Tarun Dutt, Angela Tong, Luke Ginocchio, Mahesh Bharath Keerthivasan, Steven H. Baete, Sumit Chopra, Yvonne W. Lui, Daniel K. Sodickson, Hersh Chandarana, Patricia M. Johnson:
FastMRI Prostate: A Publicly Available, Biparametric MRI Dataset to Advance Machine Learning for Prostate Cancer Imaging. CoRR abs/2304.09254 (2023) - [i8]Divyam Madaan, Daniel K. Sodickson, Kyunghyun Cho, Sumit Chopra:
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis. CoRR abs/2306.13276 (2023) - [i7]Eisa Hedayati, Fatemeh Safari, George Verghese, Vito R. Ciancia, Daniel K. Sodickson, Seena Dehkharghani, Leeor Alon:
An experimental system for detection and localization of hemorrhage using ultra-wideband microwaves with deep learning. CoRR abs/2310.02215 (2023) - 2021
- [j5]Ilias I. Giannakopoulos
Magnetic-Resonance-Based Electrical Property Mapping Using Global Maxwell Tomography With an 8-Channel Head Coil at 7 Tesla: A Simulation Study. IEEE Trans. Biomed. Eng. 68(1): 236-246 (2021) - 2020
- [j4]Florian Knoll
Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues. IEEE Signal Process. Mag. 37(1): 128-140 (2020) - [j3]José Enrique Cruz Serrallés
Noninvasive Estimation of Electrical Properties From Magnetic Resonance Measurements via Global Maxwell Tomography and Match Regularization. IEEE Trans. Biomed. Eng. 67(1): 3-15 (2020) - [c8]Anuroop Sriram
GrappaNet: Combining Parallel Imaging With Deep Learning for Multi-Coil MRI Reconstruction. CVPR 2020: 14303-14310 - [i6]Florian Knoll, Tullie Murrell, Anuroop Sriram, Nafissa Yakubova, Jure Zbontar, Michael G. Rabbat, Aaron Defazio, Matthew J. Muckley, Daniel K. Sodickson, C. Lawrence Zitnick, Michael P. Recht:
Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge. CoRR abs/2001.02518 (2020) - [i5]Taro Makino, Stanislaw Jastrzebski, Witold Oleszkiewicz, Celin Chacko, Robin Ehrenpreis, Naziya Samreen, Chloe Chhor, Eric Kim, Jiyon Lee, Kristine Pysarenko, Beatriu Reig, Hildegard Toth, Divya Awal, Linda Du, Alice Kim, James Park, Daniel K. Sodickson, Laura Heacock, Linda Moy
Differences between human and machine perception in medical diagnosis. CoRR abs/2011.14036 (2020)
2010 – 2019
- 2019
- [i4]Florian Knoll, Kerstin Hammernik, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya:
Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction. CoRR abs/1904.01112 (2019) - [i3]Anuroop Sriram, Jure Zbontar, Tullie Murrell, C. Lawrence Zitnick, Aaron Defazio, Daniel K. Sodickson:
GrappaNet: Combining Parallel Imaging with Deep Learning for Multi-Coil MRI Reconstruction. CoRR abs/1910.12325 (2019) - 2018
- [c7]Erich Kobler, Matthew J. Muckley
Variational Deep Learning for Low-Dose Computed Tomography. ICASSP 2018: 6687-6691 - [i2]Jure Zbontar, Florian Knoll, Anuroop Sriram, Matthew J. Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J. Geras, Joe Katsnelson, Hersh Chandarana, Zizhao Zhang, Michal Drozdzal, Adriana Romero, Michael G. Rabbat, Pascal Vincent, James Pinkerton, Duo Wang, Nafissa Yakubova, Erich Owens, C. Lawrence Zitnick, Michael P. Recht, Daniel K. Sodickson, Yvonne W. Lui:
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI. CoRR abs/1811.08839 (2018) - 2017
- [j2]Florian Knoll
Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer. IEEE Trans. Medical Imaging 36(1): 1-16 (2017) - [i1]Kerstin Hammernik, Teresa Klatzer, Erich Kobler, Michael P. Recht, Daniel K. Sodickson, Thomas Pock, Florian Knoll:
Learning a Variational Network for Reconstruction of Accelerated MRI Data. CoRR abs/1704.00447 (2017) - 2015
- [c6]Li Feng, Daniel K. Sodickson
Rapid free-breathing dynamic contrast-enhanced MRI using motion-resolved compressed sensing. ISBI 2015: 889-892 - [c5]Manushka V. Vaidya, Gang Chen, Bei Zhang, Christopher M. Collins, Daniel K. Sodickson
Effect of an annular sleeve of high permittivity material on resonant modes and homogeneity of a birdcage coil. ISBI 2015: 1077-1080 - [c4]Daniel K. Sodickson, Li Feng, Florian Knoll
The rapid imaging renaissance: sparser samples, denser dimensions, and glimmerings of a grand unified tomography. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2015: 94170G - 2012
- [c3]Ricardo Otazo, Li Feng, Hersh Chandarana, Tobias Block, Leon Axel, Daniel K. Sodickson:
Combination of compressed sensing and parallel imaging for highly-accelerated dynamic MRI. ISBI 2012: 980-983 - 2010
- [c2]Cagdas Bilen, Ivan W. Selesnick
On compressed sensing in parallel MRI of cardiac perfusion using temporal wavelet and TV regularization. ICASSP 2010: 630-633
2000 – 2009
- 2009
- [j1]Ricardo Otazo
Superresolution parallel magnetic resonance imaging: Application to functional and spectroscopic imaging. NeuroImage 47(1): 220-230 (2009) - 2006
- [c1]Thoralf Niendorf
Highly accelerated cardiovascular magnetic resonance imaging: concepts and clinical applications. EMBC 2006: 373-376
Coauthor Index
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