Image Segmentation of Operative Neuroanatomy Into Tissue Categories Using a Machine Learning Construct and Its Role in Neurosurgical Training

Abstract

Using the presented methods, we show that a convolutional neural network can accurately segment gross neuroanatomy images, which represents an initial foundation in artificial intelligence gross neuroanatomy that will aid future neurosurgical training. These results also suggest that our network is sufficiently robust, to an unprecedented level, for performing anatomic category recognition in a clinical setting.

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