Department of Radiology
Found 11 results
Filters: Keyword is Deep Learning  [Clear All Filters]
2023
Bae J, Li C, Masurkar A, Ge Y, Kim SGene.  2023.  Improving measurement of blood-brain barrier permeability with reduced scan time using deep-learning-derived capillary input function.. Neuroimage. 278:120284.
2022
Bae J, Huang Z, Knoll F, Geras K, Sood TPandit, Feng L, Heacock L, Moy L, Kim SGene.  2022.  Estimation of the capillary level input function for dynamic contrast-enhanced MRI of the breast using a deep learning approach.. Magn Reson Med. 87(5):2536-2550.
Gu Z, Jamison KWakefield, Khosla M, Allen EJ, Wu Y, St-Yves G, Naselaris T, Kay K, Sabuncu MR, Kuceyeski A.  2022.  NeuroGen: Activation optimized image synthesis for discovery neuroscience.. Neuroimage. 247:118812.
Cho J, Zhang J, Spincemaille P, Zhang H, Hubertus S, Wen Y, Jafari R, Zhang S, Nguyen TD, Dimov AV et al..  2022.  QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.. Magn Reson Med. 87(3):1583-1594.
2021
Jafari R, Spincemaille P, Zhang J, Nguyen TD, Luo X, Cho J, Margolis D, Prince MR, Wang Y.  2021.  Deep neural network for water/fat separation: Supervised training, unsupervised training, and no training.. Magn Reson Med. 85(4):2263-2277.
Kim SGene.  2021.  Quantitative Imaging of Body Fat Distribution in the Era of Deep Learning.. Acad Radiol. 28(11):1488-1490.
2020
Baskaran L, Al'Aref SJ, Maliakal G, Lee BC, Xu Z, Choi JW, Lee S-E, Sung JMin, Lin FY, Dunham S et al..  2020.  Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning.. PLoS One. 15(5):e0232573.
Wu N, Phang J, Park J, Shen Y, Huang Z, Zorin M, Jastrzebski S, Fevry T, Katsnelson J, Kim E et al..  2020.  Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.. IEEE Trans Med Imaging. 39(4):1184-1194.
Zhang J, Liu Z, Zhang S, Zhang H, Spincemaille P, Nguyen TD, Sabuncu MR, Wang Y.  2020.  Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction.. Neuroimage. 211:116579.
2019
Lee G, Nho K, Kang B, Sohn K-A, Kim D.  2019.  Predicting Alzheimer's disease progression using multi-modal deep learning approach.. Sci Rep. 9(1):1952.
2018
Lu D, Popuri K, Ding GWeiguang, Balachandar R, Beg MFaisal.  2018.  Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET images.. Sci Rep. 8(1):5697.