Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6920504 | Computers in Biology and Medicine | 2018 | 47 Pages |
Abstract
In this article, we first explain the concept of deep learning, addressing it in the broader context of machine learning. The most common network architectures are presented, with a more specific focus on convolutional neural networks. We then present a review of the published works on deep learning methods that can be applied to radiotherapy, which are classified into seven categories related to the patient workflow, and can provide some insights of potential future applications. We have attempted to make this paper accessible to both radiotherapy and deep learning communities, and hope that it will inspire new collaborations between these two communities to develop dedicated radiotherapy applications.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Philippe Meyer, Vincent Noblet, Christophe Mazzara, Alex Lallement,