Learning to Segment Brain Anatomy from 2D Ultrasound with Less Data
Abstract
Automatic segmentation of anatomical landmarks from ultrasound (US) plays an important role in the management of preterm neonates with a very low birth weight due to the increased risk of developing intraventricular hemorrhage (IVH) or other complications. One major problem in developing an automatic segmentation method for this task is the limited availability of annotated data. To tackle this issue, we propose a novel image synthesis method...
Paper Details
Title
Learning to Segment Brain Anatomy from 2D Ultrasound with Less Data
Published Date
Dec 17, 2019
Journal
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