Engineering a Healthier Future
Ciprian N. Ionita
PhD
Research Topics
Biomedical Imaging; Cardiovascular Disease; Diagnostic Radiology; Image Processing and Analysis; Imaging Informatics; Neurosurgery; Radiological Physics; Vascular and Interventional Radiology; Vision science
Research Expertise
- 3D Printing
- Computed Tomography and Micro-Computed Tomography
- Endovascular Devices
- Vascular Disease Diagnosis and Modeling
Grants and Sponsored Research
- October 2022–September 2024
Hemodynamically induced molecules regulating the initiation of intracranial aneurysms
Role: Co-Investigator
$438,835 - April 2020–March 2024
High Speed Angiography at 1000 frames per second
NIH
Role: Co-Investigator
$3,000,000 - August 2021–July 2023
Data-driven models to predict delayed cerebral ischemia after subarachnoid hemorrhage
NIH
Role: Co-Principal Investigator
$448,500 - July 2021–June 2023
STTR: An AI-Enhanced Angiographic System to Guide Endovascular Treatment of Intracranial Aneurysms
NSF
Role: Co-Investigator
$275,000 - January 2021–September 2022
Artificial Intelligence Quantitative Angiographic System to Guide Endovascular Procedures
NSF
Role: Principal Investigator
$50,000 - June 2020–May 2021
Quantitative angiography for real time neuro-interventional guidance
NYS
Role: Principal Investigator
$100,000 - January 2017–January 2019
Validation of a CT based FFR software using the 640 Slices Aquilion Scanner
Jacobs Institute
Role: Co-Investigator
$81,115 - August 2016–August 2017
In-Vivo feasibility testing of an Asymmetric Flow Diverter based on Solitaire AB platform for treatment of intracranial aneurysms
Medtronic-Jacobe Institute industry collaboration
Role: Principal Investigator
$93,501 - August 2012–July 2016
Microangiographic guidance of flow modifying stents - renewal
NIH
Role: Co-Investigator
$2,526,475
Patents
- METHODS AND SYSTEMS FOR ASSESSING A VASCULATURE Methods and systems are provided for assessing a vasculature of an individual. In an embodiment of a method, one or more angiographic parametric imaging (API) maps of the vasculature are obtained, wherein each API map of the one or more API maps encodes a hemodynamic parameter. A state of the vasculature is determined using a machine-learning classifier applied to the one or more API maps. (2021)
- X-ray diagnostic apparatus and medical image processing method An X ray diagnostic apparatus includes an X ray tube generating X rays, a first detector detecting the X rays, at least one second detector arranged in front of a first detection surface of the first detector and including a second detection surface narrower than the first detection surface and indicator points provided on a rear surface of the second detection surface, a projection data generation unit generating first projection data based on an output from the first detector, and a positional shift detection unit detecting a positional shift of the second detector relative to the first detector in accordance with an imaging direction by using the first projection data and a predetermined positional relationship between the points and detection elements in the second detector. (2017)