Authors
Soumya Ghose, Lois Holloway, Karen Lim, Philip Chan, Jacqueline Veera, Shalini K Vinod, Gary Liney, Peter B Greer, Jason Dowling
Publication date
2015/6/1
Source
Artificial intelligence in medicine
Volume
64
Issue
2
Pages
75-87
Publisher
Elsevier
Description
Objective
Manual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) are often necessary. However manual intervention is time consuming and may suffer from inter or intra-rater variability. In recent years a number of computer-guided automatic or semi-automatic segmentation and registration methods have been proposed. Segmentation and registration in CT and MRI for this purpose is a challenging task due to soft tissue deformation, inter-patient shape and appearance variation and anatomical changes over the course of treatment. The objective of this work is to provide a state-of-the-art review of computer-aided methods developed for adaptive treatment planning and radiation therapy planning for cervical cancer radiation therapy.
Methods
Segmentation and registration …
Total citations
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