International journal of computer assisted radiology and surgery
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Int J Comput Assist Radiol Surg · Nov 2019
Fully automated intracranial ventricle segmentation on CT with 2D regional convolutional neural network to estimate ventricular volume.
Hydrocephalus is a clinically significant condition which can have devastating consequences if left untreated. Currently available methods for quantifying this condition using CT imaging are unreliable and prone to error. The purpose of this study is to investigate the clinical utility of using convolutional neural networks to calculate ventricular volume and explore limitations. ⋯ Two-dimensional convolutional neural network architectures can be used to accurately segment and quantify intracranial ventricle volume. While further refinements are necessary, it is likely these networks could be used as a clinical tool to quantify hydrocephalus accurately and efficiently.