9 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 .…
Automated Registration of 3D Neurovascular Territory Atlas to 2D DSA for Targeted Quantitative Angiography Analysis
George Dimopoulos, Sabrina De Los Angeles Reverol Parra, Parmita Mondal +8
Subarachnoid hemorrhage (SAH), typically due to intracranial aneurysms, demands precise imaging for effective treatment. Digital Subtraction Angiography (DSA), despite being the go…
Exploring Methods for Integrating and Augmenting Multimodal Data to Improve Prognostic Accuracy in Imbalanced Datasets for Intraoperative Aneurysm Occlusion
Parisa Naghdi, Mohammad Mahdi Shiraz Bhurwani, Ahmad Rahmatpour +5
This study evaluates a multimodal machine learning framework for predicting treatment outcomes in intracranial aneurysms (IAs). Combining angiographic parametric imaging (API), pat…
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…
Injection Bias Reduction Techniques in Quantitative Angiography Using Patient-Specific Phantoms of Intracranial Aneurysm
Parmita Mondal, Kyle A Williams, Parisa Naghdi +4
In intracranial aneurysm (IA) treatment, digital subtraction angiography (DSA) monitors device-induced hemodynamic changes. Quantitative angiography (QA) provides more precise asse…
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…