Deep Learning: A Review for the Radiation Oncologist
Abstract
Introduction: Deep Learning (DL) is a machine learning technique that uses deep neural networks to create a model. The application areas of deep learning in radiation oncology include image segmentation and detection, image phenotyping, and radiomic signature discovery, clinical outcome prediction, image dose quantification, dose-response modeling, radiation adaptation, and image generation. In this review, we explain the methods used in DL and...
Paper Details
Title
Deep Learning: A Review for the Radiation Oncologist
Published Date
Oct 1, 2019
Journal
Volume
9
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