M. M. Shiraz Bhurwani

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.

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.

Feasibility of locating infarct core with 2D angiographic parametric imaging (API) using computed tomography perfusion data

C. Ionita, K. Snyder, A. Siddiqui, 2019, Medical Imaging.

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.

Initial investigation of the use of angiographic parametric imaging for early prognosis of delayed cerebral ischemia in patients with subarachnoid hemorrhage

Kelsey N. Sommer, C. Ionita, A. Siddiqui, 2022, Medical Imaging.

Quantitative angiography prognosis of intracranial aneurysm treatment failure using parametric imaging and distal vessel analysis

Kelsey N. Sommer, C. Ionita, A. Siddiqui, 2022, Medical Imaging.

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.

Initial investigation of predicting hematoma expansion for intracerebral hemorrhage using imaging biomarkers and machine learning

C. Ionita, K. Snyder, A. Siddiqui, 2022, Medical Imaging.

Prognosis of ischemia recurrence in patients with moderate intracranial atherosclerotic disease using quantitative MRA measurements

C. Ionita, J. Joseph, N. Pintér, 2022, Medical Imaging.

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.

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.

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.

Intra-operative optimal flow diverter selection for intracranial aneurysm treatment using angiographic parametric imaging: feasibility study

C. Ionita, M. M. Shiraz Bhurwani, Parmita Mondal, 2023, Medical Imaging.

Barium sulfate and pigment admixture for photoacoustic and x-ray contrast imaging of the gut

Jun Xia, C. Ionita, J. Lovell, 2023, Journal of biomedical optics.

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.

Evaluation of challenges and limitations of mechanical thrombectomy using 3D printed neurovascular phantoms

Ciprian N. Ionita, Maxim Mokin, Kelsey N. Sommer, 2021, Medical Imaging.