Peer-Reviewed Publication
Neurosurgery2025;97(3):719-726.April 14, 2025Journal Article
Estimation of Ventricular and Intracranial Hemorrhage Volumes and Midline Shift on an External Validation Data Set Using a Convolutional Neural Network Algorithm.
Marco Colasurdo1, Dor Amran2, Huanwen Chen3, Keren Ziv2, Michal Geron2, Christopher J Love2, Ariadna Robledo4, Sean O'Leary4, Adam Husain4, Nicholas Von Waaden4, Roberto Garcia4, Gautam Edhayan5, Hashem Shaltoni6, Muhammad Zeeshan Memon6, Peter Kan4
1Department of Interventional Radiology, Oregon Health and Science University, Portland , Oregon , USA.
2Viz.ai Inc., San Francisco , California , USA.
3Department of Neurology, MedStar Georgetown University Hospital, Washington , District of Columbia , USA.
4Department of Neurosurgery, The University of Texas Medical Branch, Galveston , Texas , USA.
5Department of Radiology, Division of Neuroradiology, The University of Texas Medical Branch, Galveston , Texas , USA.
6Department of Neurology, University of Texas Medical Branch, Galveston , Texas , USA.
Abstract
BACKGROUND AND OBJECTIVES: Noncontrast head computed tomography is the mainstay imaging modality to guide the management of intracranial hemorrhage (ICH); however, manual measurements can be time-consuming. In our study, we evaluate the performance of an artificial intelligence (AI) machine learning algorithm, Viz ICH-Plus, to automatically quantify ICH and bilateral lateral ventricular (BLV) volu…
Create a free account to keep reading
Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.
Want unlimited research access? See Pro plans