Artificial intelligence for automatic cerebral ventricle segmentation and volume calculation: a clinical tool for the evaluation of pediatric hydrocephalus
2020; Volume: 27; Issue: 2 Linguagem: Inglês
10.3171/2020.6.peds20251
ISSN1933-0715
AutoresJennifer L. Quon, Michelle Han, Lily H. Kim, Mary Ellen I. Koran, Leo C. Chen, Edward H. Lee, Jason L. Wright, Vijay Ramaswamy, Robert M. Lober, Michael D. Taylor, Gerald A. Grant, Samuel Cheshier, John R. W. Kestle, Michael S. B. Edwards, Kristen W. Yeom,
Tópico(s)Traumatic Brain Injury and Neurovascular Disturbances
ResumoImaging evaluation of the cerebral ventricles is important for clinical decision-making in pediatric hydrocephalus. Although quantitative measurements of ventricular size, over time, can facilitate objective comparison, automated tools for calculating ventricular volume are not structured for clinical use. The authors aimed to develop a fully automated deep learning (DL) model for pediatric cerebral ventricle segmentation and volume calculation for widespread clinical implementation across multiple hospitals.
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