| Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging GW Albers, MP Marks, S Kemp, S Christensen, JP Tsai, ... New England Journal of Medicine 378 (8), 708-718, 2018 | 4521 | 2018 |
| Recommended implementation of arterial spin‐labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL … DC Alsop, JA Detre, X Golay, M Günther, J Hendrikse, ... Magnetic resonance in medicine 73 (1), 102-116, 2015 | 2423 | 2015 |
| Comparative overview of brain perfusion imaging techniques M Wintermark, M Sesay, E Barbier, K Borbély, WP Dillon, JD Eastwood, ... Stroke 36 (9), e83-e99, 2005 | 942 | 2005 |
| MRI profile and response to endovascular reperfusion after stroke (DEFUSE 2): a prospective cohort study MG Lansberg, M Straka, S Kemp, M Mlynash, LR Wechsler, TG Jovin, ... The Lancet Neurology 11 (10), 860-867, 2012 | 893 | 2012 |
| Evidence of a cerebrovascular postarteriole windkessel with delayed compliance JB Mandeville, JJA Marota, C Ayata, G Zaharchuk, MA Moskowitz, ... Journal of Cerebral Blood Flow & Metabolism 19 (6), 679-689, 1999 | 625 | 1999 |
| Deep generative adversarial neural networks for compressive sensing MRI M Mardani, E Gong, JY Cheng, SS Vasanawala, G Zaharchuk, L Xing, ... IEEE transactions on medical imaging 38 (1), 167-179, 2018 | 601 | 2018 |
| The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification U Baid, S Ghodasara, S Mohan, M Bilello, E Calabrese, E Colak, ... arXiv preprint arXiv:2107.02314, 2021 | 572 | 2021 |
| Resting-state functional MRI: everything that nonexperts have always wanted to know H Lv, Z Wang, E Tong, LM Williams, G Zaharchuk, M Zeineh, ... American Journal of Neuroradiology 39 (8), 1390-1399, 2018 | 563 | 2018 |
| Arterial spin labeling perfusion of the brain: emerging clinical applications S Haller, G Zaharchuk, DL Thomas, KO Lovblad, F Barkhof, X Golay Radiology 281 (2), 337-356, 2016 | 496 | 2016 |
| Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features O Gevaert, LA Mitchell, AS Achrol, J Xu, S Echegaray, GK Steinberg, ... Radiology 273 (1), 168-174, 2014 | 384 | 2014 |
| Comparison of multidetector CT angiography and MR imaging of cervical artery dissection AT Vertinsky, NE Schwartz, NJ Fischbein, J Rosenberg, GW Albers, ... American Journal of Neuroradiology 29 (9), 1753-1760, 2008 | 323 | 2008 |
| Deep learning in neuroradiology G Zaharchuk, E Gong, M Wintermark, D Rubin, CP Langlotz American Journal of Neuroradiology 39 (10), 1776-1784, 2018 | 322 | 2018 |
| Deep learning enables reduced gadolinium dose for contrast‐enhanced brain MRI E Gong, JM Pauly, M Wintermark, G Zaharchuk Journal of magnetic resonance imaging 48 (2), 330-340, 2018 | 321 | 2018 |
| Arterial spin-labeling MRI can identify the presence and intensity of collateral perfusion in patients with moyamoya disease G Zaharchuk, HM Do, MP Marks, J Rosenberg, ME Moseley, ... Stroke 42 (9), 2485-2491, 2011 | 270 | 2011 |
| Imaging recommendations for acute stroke and transient ischemic attack patients: a joint statement by the American Society of Neuroradiology, the American College of Radiology … M Wintermark, PC Sanelli, GW Albers, J Bello, C Derdeyn, SW Hetts, ... American Journal of Neuroradiology 34 (11), E117-E127, 2013 | 269 | 2013 |
| Ultra–Low-Dose 18F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs KT Chen, E Gong, FB de Carvalho Macruz, J Xu, A Boumis, M Khalighi, ... Radiology 290 (3), 649-656, 2019 | 245 | 2019 |
| Hypoperfusion intensity ratio predicts infarct progression and functional outcome in the DEFUSE 2 Cohort JM Olivot, M Mlynash, M Inoue, MP Marks, HM Wheeler, S Kemp, ... Stroke 45 (4), 1018-1023, 2014 | 238 | 2014 |
| Acute stroke imaging research roadmap II M Wintermark, GW Albers, JP Broderick, AM Demchuk, JB Fiebach, ... Stroke 44 (9), 2628-2639, 2013 | 220 | 2013 |
| Arterial spin labeling MRI: clinical applications in the brain NA Telischak, JA Detre, G Zaharchuk Journal of Magnetic Resonance Imaging 41 (5), 1165-1180, 2015 | 218 | 2015 |
| Quantitative susceptibility mapping using deep neural network: QSMnet J Yoon, E Gong, I Chatnuntawech, B Bilgic, J Lee, W Jung, J Ko, H Jung, ... Neuroimage 179, 199-206, 2018 | 217 | 2018 |
