Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm

Volume: 109, Pages: 218 - 225
Published: Jun 1, 2019
Abstract
Recent analysis identified distinct genomic subtypes of lower-grade glioma tumors which are associated with shape features. In this study, we propose a fully automatic way to quantify tumor imaging characteristics using deep learning-based segmentation and test whether these characteristics are predictive of tumor genomic subtypes. We used preoperative imaging and genomic data of 110 patients from 5 institutions with lower-grade gliomas from The...
Paper Details
Title
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm
Published Date
Jun 1, 2019
Volume
109
Pages
218 - 225
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