1 citations · 1 across the 2 of their papers we have counts for
3 papers
Minimizing Human-Induced Variability in Quantitative Angiography for Robust and Explainable AI-Based Occlusion Prediction
Parmita Mondal, Mohammad Mahdi Shiraz Bhurwani, Swetadri Vasan Setlur Nagesh +7
Bias from contrast injection variability is a significant obstacle to accurate intracranial aneurysm occlusion prediction using quantitative angiography and deep neural networks .…
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…
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…