Survey on deep learning for radiotherapy

By P. Meyer, V. Noblet, C. Mazzara, A. Lallement. 2018

267 citations recorded by the source corpus.

More than 50% of cancer patients are treated with radiotherapy, either exclusively or in combination with other methods. The planning and delivery of radiotherapy treatment is a complex process, but can now be greatly facilitated by artificial intelligence technology. Deep learning is the fastest-growing field in artificial intelligence and has been successfully used in recent years in many domains, including medicine. 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.

Subfields: Pulmonary and Respiratory Medicine, Radiation, Radiology, Nuclear Medicine and Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Radiology, Nuclear Medicine and Imaging

1. Pingkun Yan
2. Uwe Kruger
3. Grant Haskins

Citations in the corpus

• An overview of deep learning in medical imaging focusing on MRI (2018, neutral): “Deep learning is applied in radiotherapy [88], in PET-MRI attenuation correction [89,90], in radiomics [91,92] (see [93] for a review of radiomics related to radiooncology and medical physics), and for theranostics in neurosurgical imaging, combining confocal laser endomicroscopy with deep learning ”
• Medical Image Segmentation Using Deep Learning: A Survey (2020, background): “[28]reviewed the advances in the application or potential application of deep learning to radiotherapy.”
• Deep learning in medical image registration: a survey (2019, background): “learning in medical image registration has not been extensively studied until the past three to four years. Though several review papers on deep learning in medical image analysis have been published [73,93,96,105,106,121,132,182], there are very few review papers that are specific to deep learning i”
• Deep learning in medical image registration: a review (2019, background): “Though several review papers on deep learning in medical image analysis have been published [73, 93, 96, 105, 106, 121, 132, 182], there are very few review papers that are specific to deep learning in medical image registration [60].”