| Assessment of computed tomography perfusion software in predicting spatial location and volume of infarct in acute ischemic stroke patients: a comparison of Sphere, Vitrea, and … RA Rava, KV Snyder, M Mokin, M Waqas, X Zhang, AR Podgorsak, ... Journal of NeuroInterventional Surgery 13 (2), 130-135, 2021 | 57 | 2021 |
| Automatic radiomic feature extraction using deep learning for angiographic parametric imaging of intracranial aneurysms AR Podgorsak, RA Rava, MMS Bhurwani, AR Chandra, JM Davies, ... Journal of neurointerventional surgery 12 (4), 417-421, 2020 | 53 | 2020 |
| Assessment of a Bayesian Vitrea CT perfusion analysis to predict final infarct and penumbra volumes in patients with acute ischemic stroke: a comparison with RAPID RA Rava, KV Snyder, M Mokin, M Waqas, AB Allman, JL Senko, ... American Journal of Neuroradiology 41 (2), 206-212, 2020 | 47 | 2020 |
| Design optimization for accurate flow simulations in 3D printed vascular phantoms derived from computed tomography angiography K Sommer, RL Izzo, L Shepard, AR Podgorsak, S Rudin, AH Siddiqui, ... Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and …, 2017 | 47 | 2017 |
| Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction MMS Bhurwani, M Waqas, AR Podgorsak, KA Williams, JM Davies, ... Journal of neurointerventional surgery 12 (7), 714-719, 2020 | 43 | 2020 |
| Initial simulated FFR investigation using flow measurements in patient-specific 3D printed coronary phantoms L Shepard, K Sommer, R Izzo, A Podgorsak, M Wilson, Z Said, FJ Rybicki, ... Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and …, 2017 | 24 | 2017 |
| CT artifact correction for sparse and truncated projection data using generative adversarial networks AR Podgorsak, MM Shiraz Bhurwani, CN Ionita Medical Physics 48 (2), 615-626, 2021 | 21 | 2021 |
| Use of quantitative angiographic methods with a data-driven model to evaluate reperfusion status (mTICI) during thrombectomy MM Shiraz Bhurwani, KV Snyder, M Waqas, M Mokin, RA Rava, ... Neuroradiology, 1-11, 2021 | 16 | 2021 |
| Effect of computed tomography perfusion post-processing algorithms on optimal threshold selection for final infarct volume prediction RA Rava, KV Snyder, M Mokin, M Waqas, AB Allman, JL Senko, ... The neuroradiology journal 33 (4), 273-285, 2020 | 14 | 2020 |
| Initial study of the radiomics of intracranial aneurysms using Angiographic Parametric Imaging (API) to evaluate contrast flow changes AR Chandra, AR Podgorsak, M Waqas, MMS Bhurwani, H Shallwani, ... Medical Imaging 2019: Physics of Medical Imaging 10948, 15-26, 2019 | 12 | 2019 |
| The Aneurysm Occlusion Assistant, an AI platform for real time surgical guidance of intracranial aneurysms KA Williams, AR Podgorsak, MMS Bhurwani, RA Rava, KN Sommer, ... Medical Imaging 2021: Imaging Informatics for Healthcare, Research, and …, 2021 | 11 | 2021 |
| Investigation of convolutional neural networks using multiple computed tomography perfusion maps to identify infarct core in acute ischemic stroke patients RA Rava, AR Podgorsak, M Waqas, KV Snyder, M Mokin, EI Levy, ... Journal of Medical Imaging 8 (1), 014505-014505, 2021 | 10 | 2021 |
| Enhancing performance of a computed tomography perfusion software for improved prediction of final infarct volume in acute ischemic stroke patients RA Rava, KV Snyder, M Mokin, M Waqas, AR Podgorsak, AB Allman, ... The Neuroradiology Journal 34 (3), 222-237, 2021 | 9 | 2021 |
| Use of biplane quantitative angiographic imaging with ensemble neural networks to assess reperfusion status during mechanical thrombectomy MMS Bhurwani, KV Snyder, M Waqas, M Mokin, RA Rava, AR Podgorsak, ... Medical Imaging 2021: Computer-Aided Diagnosis 11597, 328-336, 2021 | 9 | 2021 |
| Initial evaluation of a convolutional neural network used for noninvasive assessment of coronary artery disease severity from coronary computed tomography angiography data AR Podgorsak, KN Sommer, A Reddy, V Iyer, MF Wilson, FJ Rybicki, ... Medical Physics 47 (9), 3996-4004, 2020 | 9 | 2020 |
| Use of a convolutional neural network to identify infarct core using computed tomography perfusion parameters RA Rava, AR Podgorsak, M Waqas, KV Snyder, EI Levy, JM Davies, ... Medical Imaging 2021: Image Processing 11596, 269-281, 2021 | 8 | 2021 |
| Feasibility study of deep neural networks to classify intracranial aneurysms using angiographic parametric imaging MMS Bhurwani, AR Podgorsak, AR Chandra, RA Rava, KV Snyder, ... Medical Imaging 2019: Computer-Aided Diagnosis 10950, 584-597, 2019 | 8 | 2019 |
| Feasibility study of deep neural networks to classify intracranial aneurysms using angiographic parametric imaging MMS Bhurwani, AR Podgorsak, AR Chandra, RA Rava, KV Snyder, ... Medical Imaging 2019: Computer-Aided Diagnosis 10950, 584-597, 2019 | 8 | 2019 |
| Implementation of material decomposition using an EMCCD and CMOS-based micro-CT system AR Podgorsak, SVS Nagesh, DR Bednarek, S Rudin, CN Ionita Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and …, 2017 | 7 | 2017 |
| Predicting treatment outcome of intracranial aneurysms using angiographic parametric imaging and recurrent neural networks MMS Bhurwani, M Waqas, KA Williams, RA Rava, AR Podgorsak, ... Medical Imaging 2020: Computer-Aided Diagnosis 11314, 610-619, 2020 | 6 | 2020 |
