Publications by authors named "S Arabshahi"
Background: Mild traumatic brain injury is theorized to cause widespread functional changes to the brain. Resting-state fMRI may be able to measure functional connectivity changes after traumatic brain injury, but resting-state fMRI studies are heterogeneous, using numerous techniques to study ROIs across various resting-state networks.
Purpose: We systematically reviewed the literature to ascertain whether adult patients who have experienced mild traumatic brain injury show consistent functional connectivity changes on resting-state -fMRI, compared with healthy patients.
Background And Purpose: Several recent works using resting-state fMRI suggest possible alterations of resting-state functional connectivity after mild traumatic brain injury. However, the literature is plagued by various analysis approaches and small study cohorts, resulting in an inconsistent array of reported findings. In this study, we aimed to investigate differences in whole-brain resting-state functional connectivity between adult patients with mild traumatic brain injury within 1 month of injury and healthy control subjects using several comprehensive resting-state functional connectivity measurement methods and analyses.
View Article and Find Full Text PDFObjective: We prospectively determined incident cardiovascular events and their association with risk factors in rural India.
Methods: We followed up with 7935 adults from the Rishi Valley Prospective Cohort Study to identify incident cardiovascular events. Using Cox proportional hazards regression, we estimated hazard ratios (HRs) with 95% confidence intervals (95% CI) for associations between potential risk factors and cardiovascular events.
Aims: We compared the performance of cardiovascular risk prediction tools in rural India.
Methods And Results: We applied the World Health Organization Risk Score (WHO-RS) tools, Australian Risk Score (ARS), and Global risk (Globorisk) prediction tools to participants aged 40-74 years, without prior cardiovascular disease, in the Rishi Valley Prospective Cohort Study, Andhra Pradesh, India. Cardiovascular events during the 5-year follow-up period were identified by verbal autopsy (fatal events) or self-report (non-fatal events).
Improving across-dataset brain tissue segmentation for MRI imaging using transformer.
Front Neuroimaging
November 2022
Article Synopsis
- This study addresses the challenges of manual brain tissue segmentation in MRI data analysis and highlights the limitations of existing automated methods, especially CNNs, in achieving reliable results.
- The authors introduce a new hybrid CNN-Transformer architecture that enhances performance for 3D medical image segmentation, demonstrating its effectiveness on diverse T1-weighted MRI datasets.
- The model's robustness is validated across multiple sites and conditions, showing superior generality and reliability, making it a promising tool for brain research and available for public access via GitHub.