| Comprehensive quantification of signal‐to‐noise ratio and g‐factor for image‐based and k‐space‐based parallel imaging reconstructions PM Robson, AK Grant, AJ Madhuranthakam, R Lattanzi, DK Sodickson, ... Magnetic Resonance in Medicine: An Official Journal of the International …, 2008 | 565 | 2008 |
| Modeling Renal Cell Carcinoma in Mice: Bap1 and Pbrm1 Inactivation Drive Tumor Grade YF Gu, S Cohn, A Christie, T McKenzie, N Wolff, QN Do, ... Cancer discovery 7 (8), 900-917, 2017 | 169 | 2017 |
| HIF-2 complex dissociation, target inhibition, and acquired resistance with PT2385, a first-in-class HIF-2 inhibitor, in patients with clear cell renal cell carcinoma KD Courtney, Y Ma, A Diaz de Leon, A Christie, Z Xie, L Woolford, ... Clinical Cancer Research 26 (4), 793-803, 2020 | 167 | 2020 |
| Retracted: A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas CG Bangalore Yogananda, BR Shah, M Vejdani-Jahromi, SS Nalawade, ... Neuro-oncology 22 (3), 402-411, 2020 | 160 | 2020 |
| Magnetic resonance neurography: current perspectives and literature review A Chhabra, AJ Madhuranthakam, G Andreisek European radiology 28, 698-707, 2018 | 152 | 2018 |
| Consensus-based technical recommendations for clinical translation of renal ASL MRI F Nery, CE Buchanan, AA Harteveld, A Odudu, O Bane, EF Cox, K Derlin, ... Magnetic Resonance Materials in Physics, Biology and Medicine 33, 141-161, 2020 | 146 | 2020 |
| Strategies for reducing respiratory motion artifacts in renal perfusion imaging with arterial spin labeling PM Robson, AJ Madhuranthakam, W Dai, I Pedrosa, NM Rofsky, ... Magnetic Resonance in Medicine: An Official Journal of the International …, 2009 | 144 | 2009 |
| MRI-based deep-learning method for determining glioma MGMT promoter methylation status CGB Yogananda, BR Shah, SS Nalawade, GK Murugesan, FF Yu, ... American Journal of Neuroradiology 42 (5), 845-852, 2021 | 100 | 2021 |
| A fully automated deep learning network for brain tumor segmentation CGB Yogananda, BR Shah, M Vejdani-Jahromi, SS Nalawade, ... Tomography 6 (2), 186, 2020 | 80 | 2020 |
| MR neurography of brachial plexus at 3.0 T with robust fat and blood suppression X Wang, C Harrison, YK Mariappan, K Gopalakrishnan, A Chhabra, ... Radiology 283 (2), 538-546, 2017 | 75 | 2017 |
| CEST‐Dixon for human breast lesion characterization at 3 T: A preliminary study S Zhang, S Seiler, X Wang, AJ Madhuranthakam, J Keupp, EE Knippa, ... Magnetic resonance in medicine 80 (3), 895-903, 2018 | 70 | 2018 |
| Recent technical developments in ASL: a review of the state of the art L Hernandez‐Garcia, V Aramendía‐Vidaurreta, DS Bolar, W Dai, ... Magnetic resonance in medicine 88 (5), 2021-2042, 2022 | 65 | 2022 |
| Added value of diffusion-weighted acquisitions in MRI of the abdomen and pelvis WA Moore, G Khatri, AJ Madhuranthakam, RD Sims, I Pedrosa American Journal of Roentgenology 202 (5), 995-1006, 2014 | 63 | 2014 |
| Tumor vascularity in renal masses: correlation of arterial spin-labeled and dynamic contrast-enhanced magnetic resonance imaging assessments Y Zhang, P Kapur, Q Yuan, Y Xi, I Carvo, S Signoretti, I Dimitrov, ... Clinical genitourinary cancer 14 (1), e25-e36, 2016 | 62 | 2016 |
| Volumetric arterial spin-labeled perfusion imaging of the kidneys with a three-dimensional fast spin echo acquisition PM Robson, AJ Madhuranthakam, MP Smith, MRM Sun, W Dai, ... Academic radiology 23 (2), 144-154, 2016 | 60 | 2016 |
| A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas CGB Yogananda, BR Shah, FF Yu, MC Pinho, SS Nalawade, ... Neuro-oncology advances 2 (Supplement_4), iv42-iv48, 2020 | 59 | 2020 |
| MRI of the placenta accreta spectrum (PAS) disorder: radiomics analysis correlates with surgical and pathological outcome QN Do, MA Lewis, Y Xi, AJ Madhuranthakam, SK Happe, JS Dashe, ... Journal of Magnetic Resonance Imaging 51 (3), 936-946, 2020 | 54 | 2020 |
| QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation-analysis of ranking scores and benchmarking results R Mehta, A Filos, U Baid, C Sako, R McKinley, M Rebsamen, K Dätwyler, ... The journal of machine learning for biomedical imaging 2022, 2022 | 53 | 2022 |
| Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI Y Zhang, D Udayakumar, L Cai, Z Hu, P Kapur, EY Kho, A Pavía-Jiménez, ... JCI insight 2 (15), 2017 | 49 | 2017 |
| Current utilities of imaging in grading musculoskeletal soft tissue sarcomas SM Fisher, R Joodi, AJ Madhuranthakam, OK Öz, R Sharma, A Chhabra European journal of radiology 85 (7), 1336-1344, 2016 | 43 | 2016 |
Charles McKenzieThe University of Western Ontariouwo.ca의 이메일 확인됨