| Deep learning for prediction of obstructive disease from fast myocardial perfusion SPECT: a multicenter study J Betancur, F Commandeur, M Motlagh, T Sharir, AJ Einstein, S Bokhari, ... JACC: Cardiovascular Imaging 11 (11), 1654-1663, 2018 | 340 | 2018 |
| Pericoronary adipose tissue computed tomography attenuation and high-risk plaque characteristics in acute coronary syndrome compared with stable coronary artery disease M Goeller, S Achenbach, S Cadet, AC Kwan, F Commandeur, PJ Slomka, ... JAMA cardiology 3 (9), 858-863, 2018 | 250 | 2018 |
| Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects M Goeller, S Achenbach, M Marwan, MK Doris, S Cadet, F Commandeur, ... Journal of cardiovascular computed tomography 12 (1), 67-73, 2018 | 205 | 2018 |
| Deep learning for quantification of epicardial and thoracic adipose tissue from non-contrast CT F Commandeur, M Goeller, J Betancur, S Cadet, M Doris, X Chen, ... IEEE transactions on medical imaging 37 (8), 1835-1846, 2018 | 197 | 2018 |
| Haralick textural features on T2‐weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer K Gnep, A Fargeas, RE Gutiérrez‐Carvajal, F Commandeur, R Mathieu, ... Journal of Magnetic Resonance Imaging 45 (1), 103-117, 2017 | 183 | 2017 |
| Relationship between changes in pericoronary adipose tissue attenuation and coronary plaque burden quantified from coronary computed tomography angiography M Goeller, BK Tamarappoo, AC Kwan, S Cadet, F Commandeur, ... European Heart Journal-Cardiovascular Imaging 20 (6), 636-643, 2019 | 182 | 2019 |
| Deep learning analysis of upright-supine high-efficiency SPECT myocardial perfusion imaging for prediction of obstructive coronary artery disease: a multicenter study J Betancur, LH Hu, F Commandeur, T Sharir, AJ Einstein, MB Fish, ... Journal of Nuclear Medicine 60 (5), 664-670, 2019 | 143 | 2019 |
| Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective … F Commandeur, PJ Slomka, M Goeller, X Chen, S Cadet, A Razipour, ... Cardiovascular Research, 2019 | 129 | 2019 |
| Fully automated CT quantification of epicardial adipose tissue by deep learning: a multicenter study F Commandeur, M Goeller, A Razipour, S Cadet, MM Hell, J Kwiecinski, ... Radiology: Artificial Intelligence 1 (6), e190045, 2019 | 118 | 2019 |
| Deep learning–based quantification of epicardial adipose tissue volume and attenuation predicts major adverse cardiovascular events in asymptomatic subjects E Eisenberg, PA McElhinney, F Commandeur, X Chen, S Cadet, ... Circulation: Cardiovascular Imaging 13 (2), e009829, 2020 | 114 | 2020 |
| Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry LH Hu, J Betancur, T Sharir, AJ Einstein, S Bokhari, MB Fish, TD Ruddy, ... European Heart Journal-Cardiovascular Imaging 21 (5), 549-559, 2020 | 89 | 2020 |
| Evaluation of multi-atlas-based segmentation of CT scans in prostate cancer radiotherapy O Acosta, A Simon, F Monge, F Commandeur, C Bassirou, G Cazoulat, ... 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro …, 2011 | 66 | 2011 |
| Deep learning-based stenosis quantification from coronary CT angiography Y Hong, F Commandeur, S Cadet, M Goeller, MK Doris, X Chen, ... Proceedings of Spie--the International Society for Optical Engineering 10949 …, 2019 | 55 | 2019 |
| Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECT LH Hu, RJH Miller, T Sharir, F Commandeur, R Rios, AJ Einstein, MB Fish, ... European Heart Journal-Cardiovascular Imaging 22 (6), 705-714, 2021 | 54 | 2021 |
| Machine learning integration of circulating and imaging biomarkers for explainable patient-specific prediction of cardiac events: A prospective study BK Tamarappoo, A Lin, F Commandeur, PA McElhinney, S Cadet, ... Atherosclerosis 318, 76-82, 2021 | 51 | 2021 |
| Metabolic syndrome, fatty liver, and artificial intelligence-based epicardial adipose tissue measures predict long-term risk of cardiac events: a prospective study A Lin, ND Wong, A Razipour, PA McElhinney, F Commandeur, SJ Cadet, ... Cardiovascular diabetology 20, 1-11, 2021 | 50 | 2021 |
| MRI to CT prostate registration for improved targeting in cancer external beam radiotherapy F Commandeur, A Simon, R Mathieu, M Nassef, JDO Arango, Y Rolland, ... IEEE journal of biomedical and health informatics 21 (4), 1015-1026, 2016 | 35 | 2016 |
| A VTK algorithm for the computation of the Hausdorff distance F Commandeur, J Velut, O Acosta VTK J 839, 2011 | 33 | 2011 |
| Machine learning in predicting coronary heart disease and cardiovascular disease events: results from the multi-ethnic study of atherosclerosis (mesa) R Nakanishi, D Dey, F Commandeur, P Slomka, J Betancur, H Gransar, ... Journal of the American College of Cardiology 71 (11S), A1483-A1483, 2018 | 29 | 2018 |
| Population model of bladder motion and deformation based on dominant eigenmodes and mixed-effects models in prostate cancer radiotherapy R Rios, R De Crevoisier, JD Ospina, F Commandeur, C Lafond, A Simon, ... Medical image analysis 38, 133-149, 2017 | 29 | 2017 |
Damini DeyBiomedical Imaging Research Institute, Cedars-Sinai Medical CenterE-mail confirmado em cshs.org