| Two-branch recurrent network for isolating deepfakes in videos I Masi, A Killekar, RM Mascarenhas, SP Gurudatt, W AbdAlmageed Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 473 | 2020 |
| Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study A Lin, N Manral, P McElhinney, A Killekar, H Matsumoto, J Kwiecinski, ... The Lancet Digital Health 4 (4), e256-e265, 2022 | 179 | 2022 |
| Deep learning of coronary calcium scores from PET/CT attenuation maps accurately predicts adverse cardiovascular events K Pieszko, A Shanbhag, A Killekar, RJH Miller, M Lemley, Y Otaki, ... Cardiovascular Imaging 16 (5), 675-687, 2023 | 41 | 2023 |
| Deep Learning Coronary Artery Calcium Scores from SPECT/CT Attenuation Maps Improve Prediction of Major Adverse Cardiac Events RJH Miller, K Pieszko, A Shanbhag, A Feher, M Lemley, A Killekar, ... Journal of Nuclear Medicine 64 (4), 652-658, 2023 | 32 | 2023 |
| Deep learning for explainable estimation of mortality risk from myocardial positron emission tomography images A Singh, J Kwiecinski, RJH Miller, Y Otaki, PB Kavanagh, ... Circulation: Cardiovascular Imaging 15 (9), e014526, 2022 | 26 | 2022 |
| Automated nonlinear registration of coronary PET to CT angiography using pseudo-CT generated from PET with generative adversarial networks A Singh, J Kwiecinski, S Cadet, A Killekar, E Tzolos, MC Williams, ... Journal of Nuclear Cardiology 30 (2), 604-615, 2023 | 21 | 2023 |
| AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging RJH Miller, A Shanbhag, A Killekar, M Lemley, B Bednarski, ... JACC: Cardiovascular Imaging, 2024 | 15 | 2024 |
| AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging RJH Miller, A Shanbhag, A Killekar, M Lemley, B Bednarski, ... NPJ Digital Medicine 7 (1), 24, 2024 | 13 | 2024 |
| Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography RJH Miller, A Killekar, A Shanbhag, B Bednarski, AM Michalowska, ... Nature Communications 15 (1), 2747, 2024 | 10 | 2024 |
| Automated vessel-specific coronary artery calcification quantification with deep learning in a large multi-centre registry MC Williams, AD Shanbhag, J Zhou, AM Michalowska, M Lemley, ... European Heart Journal-Cardiovascular Imaging, jeae045, 2024 | 8 | 2024 |
| Calcium scoring in low-dose ungated chest CT scans using convolutional long-short term memory networks K Pieszko, A Shanbhag, A Killekar, M Lemley, Y Otaki, S Van Kriekinge, ... Medical Imaging 2022: Image Processing 12032, 865-871, 2022 | 7 | 2022 |
| Deep Learning From Coronary Computed Tomography Angiography for Atherosclerotic Plaque and Stenosis Quantification and Cardiac Risk Prediction A Lin, N Manral, P McElhinney, A Killekar, H Matsumoto, J Kwiecinski, ... | 7 | 2022 |
| Radiomorphological signs and clinical severity of SARS-CoV-2 lineage B. 1.1. 7 J Simon, K Grodecki, S Cadet, A Killekar, P Slomka, SJ Zara, ... BJR| Open 4 (1), 20220016, 2022 | 5 | 2022 |
| AI for multistructure incidental findings and mortality prediction at chest CT in lung cancer screening AM Marcinkiewicz, M Buchwald, A Shanbhag, BP Bednarski, A Killekar, ... Radiology 312 (3), e240541, 2024 | 4 | 2024 |
| Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional LSTM networks. K Grodecki, A Killekar, A Lin, S Cadet, P McElhinney, A Razipour, C Chan, ... ArXiv, 2021 | 4 | 2021 |
| Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems K Grodecki, A Killekar, J Simon, A Lin, S Cadet, P McElhinney, C Chan, ... The British Journal of Radiology 96 (1149), 20220180, 2023 | 3 | 2023 |
| Comparative analysis between convolutional long short-term memory networks and vision transformers for coronary calcium scoring in non-contrast CT AD Shanbhag, K Pieszko, RJH Miller, A Killekar, W Parker, H Gransar, ... Medical Imaging 2023: Image Processing 12464, 89-92, 2023 | 3 | 2023 |
| Patient-Specific Myocardial Infarction Risk Thresholds From AI-Enabled Coronary Plaque Analysis RJH Miller, N Manral, A Lin, A Shanbhag, C Park, J Kwiecinski, A Killekar, ... Circulation: Cardiovascular Imaging 17 (10), e016958, 2024 | 2 | 2024 |
| Artificial intelligence-based plaque quantification from coronary computed tomography angiography using deep learning: External validation and comparison with intravascular … A Lin, N Manral, P McElhinney, A Killekar, H Matsumoto, J Kwiecinski, ... Journal of Cardiovascular Computed Tomography 15 (4), S5-S6, 2021 | 2 | 2021 |
| Pseudo-contrast cardiac CT angiography derived from non-contrast CT using conditional generative adversarial networks A Killekar, J Kwiecinski, M Kruk, C Kepka, A Shanbhag, D Dey, P Slomka Medical Imaging 2023: Image Processing 12464, 792-798, 2023 | 1 | 2023 |
