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An evaluation of atlas selection methods for atlas-based automatic segmentation in radiotherapy treatment planning.

08:00 EDT 9th April 2019 | BioPortfolio

Summary of "An evaluation of atlas selection methods for atlas-based automatic segmentation in radiotherapy treatment planning."

Atlas-based automatic segmentation is used in radiotherapy planning to accelerate the delineation of organs at risk (OARs). Atlas selection has been proposed as a way to improve the accuracy and execution time of segmentation, assuming that, the more similar the atlas is to the patient, the better the results will be. This work presents an analysis of atlas selection methods in the context of radiotherapy treatment planning. For a range of commonly contoured OARs, a thorough comparison of a large class of typical atlas selection methods has been performed. For this evaluation, clinically contoured CT images of the head and neck (N=316) and thorax (N=280) were used. State-of-the-art intensity and deformation similarity-based atlas selection methods were found to compare poorly to perfect atlas selection. Counter-intuitively, atlas selection methods based on a fixed set of representative atlases outperformed atlas selection methods based on the patient image. This study suggests that atlas-based segmentation with currently available selection methods compares poorly to the potential best performance, hampering the clinical utility of atlas-based segmentation. Effective atlas selection remains an open challenge in atlas-based segmentation for radiotherapy planning.

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This article was published in the following journal.

Name: IEEE transactions on medical imaging
ISSN: 1558-254X
Pages:

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