Članki z zahtevami za javni dostop - Benjamin C. LeeVeč o tem
Na voljo nekje: 14
Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography …
SJ Al’Aref, G Maliakal, G Singh, AR van Rosendael, X Ma, Z Xu, ...
European heart journal 41 (3), 359-367, 2020
Zahteve: US National Institutes of Health
Quantification of Myocardial Blood Flow in Absolute Terms Using 82Rb PET Imaging: The RUBY-10 Study
SV Nesterov, E Deshayes, R Sciagrà, L Settimo, JM Declerck, XB Pan, ...
JACC: Cardiovascular Imaging 7 (11), 1119-1127, 2014
Zahteve: US National Institutes of Health, Academy of Finland
Comparison and prognostic validation of multiple methods of quantification of myocardial blood flow with 82Rb PET
VL Murthy, BC Lee, A Sitek, M Naya, J Moody, V Polavarapu, EP Ficaro, ...
J Nucl Med 55, 1952-1958, 2014
Zahteve: US National Institutes of Health
Absolute myocardial flow quantification with 82Rb PET/CT: comparison of different software packages and methods
AK Tahari, A Lee, M Rajaram, K Fukushima, MA Lodge, BC Lee, ...
European journal of nuclear medicine and molecular imaging 41, 126-135, 2014
Zahteve: US National Institutes of Health
Identification and quantification of cardiovascular structures from CCTA: an end-to-end, rapid, pixel-wise, deep-learning method
L Baskaran, G Maliakal, SJ Al’Aref, G Singh, Z Xu, K Michalak, K Dolan, ...
Cardiovascular Imaging 13 (5), 1163-1171, 2020
Zahteve: US National Institutes of Health
Characterization of 3-dimensional PET systems for accurate quantification of myocardial blood flow
JM Renaud, K Yip, J Guimond, M Trottier, P Pibarot, E Turcotte, C Maguire, ...
Journal of Nuclear Medicine 58 (1), 103-109, 2017
Zahteve: Canadian Institutes of Health Research, Heart and Stroke Foundation of Canada
Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning
L Baskaran, SJ Al’Aref, G Maliakal, BC Lee, Z Xu, JW Choi, SE Lee, ...
PloS one 15 (5), e0232573, 2020
Zahteve: US National Institutes of Health
A boosted ensemble algorithm for determination of plaque stability in high-risk patients on coronary CTA
SJ Al’Aref, G Singh, JW Choi, Z Xu, G Maliakal, AR van Rosendael, ...
Cardiovascular Imaging 13 (10), 2162-2173, 2020
Zahteve: US National Institutes of Health
Blood pool and tissue phase patient motion effects on 82rubidium PET myocardial blood flow quantification
BC Lee, JB Moody, A Poitrasson-Rivière, AC Melvin, RL Weinberg, ...
Journal of Nuclear Cardiology 26 (6), 1918-1929, 2019
Zahteve: US National Institutes of Health
Automated dynamic motion correction using normalized gradient fields for 82 rubidium PET myocardial blood flow quantification
BC Lee, JB Moody, A Poitrasson-Rivière, AC Melvin, RL Weinberg, ...
Journal of Nuclear Cardiology 27 (6), 1982-1998, 2020
Zahteve: US National Institutes of Health
Extraction of radiographic findings from unstructured thoracoabdominal computed tomography reports using convolutional neural network based natural language processing
M Pandey, Z Xu, E Sholle, G Maliakal, G Singh, Z Fatima, D Larine, ...
PLoS One 15 (7), e0236827, 2020
Zahteve: US National Institutes of Health
Machine learning insight into the role of imaging and clinical variables for the prediction of obstructive coronary artery disease and revascularization: An exploratory …
L Baskaran, X Ying, Z Xu, SJ Al’Aref, BC Lee, SE Lee, I Danad, HB Park, ...
PLoS One 15 (6), e0233791, 2020
Zahteve: US National Institutes of Health
Optimization of temporal sampling for 82rubidium PET myocardial blood flow quantification
BC Lee, JB Moody, RL Weinberg, JR Corbett, EP Ficaro, VL Murthy
Journal of Nuclear Cardiology 24 (5), 1517-1529, 2017
Zahteve: US National Institutes of Health
Mortality impact of low CAC density predominantly occurs in early atherosclerosis: explainable ML in the CAC consortium
FY Lin, BP Goebel, BC Lee, Y Lu, L Baskaran, YE Yoon, GT Maliakal, ...
Journal of cardiovascular computed tomography 17 (1), 28-33, 2023
Zahteve: US National Institutes of Health
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