A. Podgorsak

发表

Automatic radiomic feature extraction using deep learning for angiographic parametric imaging of intracranial aneurysms

Ciprian N Ionita, Adnan H Siddiqui, Mohammad Mahdi Shiraz Bhurwani, 2019, Journal of NeuroInterventional Surgery.

Initial evaluation of a convolutional neural network used for non-invasive assessment of coronary artery disease severity from coronary computed tomography angiography data.

Kelsey N. Sommer, F. Rybicki, D. Mitsouras, 2020, Medical physics.

Enhancing performance of a computed tomography perfusion software for improved prediction of final infarct volume in acute ischemic stroke patients

C. Ionita, M. Mokin, K. Snyder, 2021, The neuroradiology journal.

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 RAPID

Xiaoliang Zhang, C. Ionita, M. Mokin, 2020, Journal of NeuroInterventional Surgery.

Effect of computed tomography perfusion post-processing algorithms on optimal threshold selection for final infarct volume prediction

C. Ionita, M. Mokin, K. Snyder, 2020, The neuroradiology journal.

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

M. Mokin, K. Snyder, A. Siddiqui, 2020, American Journal of Neuroradiology.

Investigation of the efficacy of a data-driven CT artifact correction scheme for sparse and truncated projection data for intracranial hemorrhage diagnosis.

C. Ionita, A. Podgorsak, M. M. Shiraz Bhurwani, 2021, Proceedings of SPIE--the International Society for Optical Engineering.

Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction

Kyle A. Williams, C. Ionita, K. Snyder, 2019, Journal of NeuroInterventional Surgery.

Initial study of the radiomics of intracranial aneurysms using Angiographic Parametric Imaging (API) to evaluate contrast flow changes

Stephen Rudin, Alexander R. Podgorsak, Ciprian N. Ionita, 2019, Medical Imaging.

CT artifact correction for sparse and truncated projection data using generative adversarial networks.

Ciprian N Ionita, Mohammad Mahdi Shiraz Bhurwani, Alexander R Podgorsak, 2020, Medical physics.

Investigation of convolutional neural networks using multiple computed tomography perfusion maps to identify infarct core in acute ischemic stroke patients

Alexander R. Podgorsak, Ciprian N. Ionita, Jason M. Davies, 2021, Journal of medical imaging.

Use of quantitative angiographic methods with a data-driven model to evaluate reperfusion status (mTICI) during thrombectomy

C. Ionita, M. Mokin, K. Snyder, 2021, Neuroradiology.

Semi-supervised Planning Method for Breast Electronic Tissue Compensation Treatments Based on Breast Radius and Separation

A. Podgorsak, L. Kumaraswamy, 2020, Radiology and oncology.

Use of 3D printed intracranial aneurysm phantoms to test the effect of flow diverters geometry on hemodynamics

Alexander R. Podgorsak, Ciprian N. Ionita, Ryan A. Rava, 2020, Medical Imaging.

Use of a CMOS-based micro-CT system to validate a ring artifact correction algorithm on low-dose image data

Stephen Rudin, Alexander R. Podgorsak, Ciprian N. Ionita, 2018, Medical Imaging.

Investigation of noise and contrast sensitivity of an electron multiplying charge-coupled device (EMCCD) based cone beam micro-CT system

Daniel R. Bednarek, Stephen Rudin, Alexander R. Podgorsak, 2016, SPIE Medical Imaging.

Dosimetric and workflow impact of synthetic-MRI use in prostate high-dose-rate brachytherapy.

J. Roeske, M. Harkenrider, Hyejoo Kang, 2023, Brachytherapy.

X-ray image guidance workflow development for in-vivo aneurysm treatment using a new retrievable asymmetric flow diverter (RAFD)

Alexander R. Podgorsak, Ciprian N. Ionita, Lauren M. Shepard, 2018, Medical Imaging.

Use of a convolutional neural network to identify infarct core using computed tomography perfusion parameters

Alexander R. Podgorsak, Ciprian N. Ionita, Jason M. Davies, 2021, Medical Imaging.

Use of biplane quantitative angiographic imaging with ensemble neural networks to assess reperfusion status during mechanical thrombectomy

Alexander R. Podgorsak, Ciprian N. Ionita, Jason M. Davies, 2021, Medical Imaging.

Investigation of the accuracy of classifying coronary artery disease severity using machine learning with subdomain analysis of fractional flow reserve diagnosis in patients

Alexander R. Podgorsak, Ciprian N. Ionita, Dimitrios Mitsouras, 2020, Medical Imaging.

Feasibility study of deep neural networks to classify intracranial aneurysms using angiographic parametric imaging

Alexander R. Podgorsak, Ciprian N. Ionita, Jason M. Davies, 2019, Medical Imaging.