4 papers
Leveraging Convolutional Neural Networks for 3D Quantitative Angiography Reconstructions from Sparse Cone Beam CT Projections Utilizing CFD Data
Ahmad Rahmatpour, Allison Shields, Parmita Mondal +6
This study leverages convolutional neural networks to enhance the temporal resolution of 3D angiography in intracranial aneurysms focusing on the reconstruction of volumetric contr…
Analysis of Quantitative Angiography using Projection Foreshortening Correction and Injection Bias Removal
Parmita Mondal, Allison Shields, Mohammad Mahdi Shiraz Bhurwani +4
This study aims to mitigate these biases and enhance QA analysis by applying a path-length correction (PLC) correction, followed by singular value decomposition (SVD)-based deconvo…
In-Silico Analysis of Curve Fitting in Angiographic Parametric Imaging in Intracranial Aneurysms
Parmita Mondal, Allison Shields, Mohammad Mahdi Shiraz Bhurwani +2
In Angiographic Parametric Imaging (API), accurate estimation of parameters from Time Density Curves (TDC) is crucial. However, these estimations are often marred by errors arising…
Effect of Singular Value Decomposition Algorithms on Removing Injection Variability in 2D Quantitative Angiography of Intracranial Aneurysms
Parmita Mondal, Swetadri Vasan Setlur Nagesh, Sam Sommers-Thaler +8
Intraoperative 2D quantitative angiography (QA) for intracranial aneurysms (IAs) has accuracy challenges due to the variability of hand injections. Despite the success of singular…