| Evaluation of multiple-atlas-based strategies for segmentation of the thyroid gland in head and neck CT images for IMRT. | |
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MedLine Citation:
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PMID: 22126838 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Segmenting the thyroid gland in head and neck CT images is of vital clinical significance in designing intensity-modulated radiation therapy (IMRT) treatment plans. In this work, we evaluate and compare several multiple-atlas-based methods to segment this structure. Using the most robust method, we generate automatic segmentations for the thyroid gland and study their clinical applicability. The various methods we evaluate range from selecting a single atlas based on one of three similarity measures, to combining the segmentation results obtained with several atlases and weighting their contribution using techniques including a simple majority vote rule, a technique called STAPLE that is widely used in the medical imaging literature, and the similarity between the atlas and the volume to be segmented. We show that the best results are obtained when several atlases are combined and their contributions are weighted with a measure of similarity between each atlas and the volume to be segmented. We also show that with our data set, STAPLE does not always lead to the best results. Automatic segmentations generated by the combination method using the correlation coefficient (CC) between the deformed atlas and the patient volume, which is the most accurate and robust method we evaluated, are presented to a physician as 2D contours and modified to meet clinical requirements. It is shown that about 40% of the contours of the left thyroid and about 42% of the right thyroid can be used directly. An additional 21% on the left and 24% on the right require only minimal modification. The amount and the location of the modifications are qualitatively and quantitatively assessed. We demonstrate that, although challenged by large inter-subject anatomical discrepancy, atlas-based segmentation of the thyroid gland in IMRT CT images is feasible by involving multiple atlases. The results show that a weighted combination of segmentations by atlases using the CC as the similarity measure slightly outperforms standard combination methods, e.g. the majority vote rule and STAPLE, as well as methods selecting a single most similar atlas. The results we have obtained suggest that using our contours as initial contours to be edited has clinical value. |
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Authors:
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A Chen; K J Niermann; M A Deeley; B M Dawant |
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Publication Detail:
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Type: Evaluation Studies; Journal Article; Research Support, N.I.H., Extramural Date: 2011-11-29 |
Journal Detail:
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Title: Physics in medicine and biology Volume: 57 ISSN: 1361-6560 ISO Abbreviation: Phys Med Biol Publication Date: 2012 Jan |
Date Detail:
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Created Date: 2011-12-14 Completed Date: 2012-04-09 Revised Date: 2012-04-26 |
Medline Journal Info:
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Nlm Unique ID: 0401220 Medline TA: Phys Med Biol Country: England |
Other Details:
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Languages: eng Pagination: 93-111 Citation Subset: IM |
Affiliation:
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Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA. antong.chen@vanderbilt.edu |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Head and Neck Neoplasms
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radiography*,
radiotherapy* Humans Image Processing, Computer-Assisted / methods* Laryngeal Neoplasms / radiography, radiotherapy Radiotherapy, Intensity-Modulated / methods* Thyroid Gland / radiography* Tomography, X-Ray Computed / methods* Tongue Neoplasms / radiography, radiotherapy |
| Grant Support | |
ID/Acronym/Agency:
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R01EB006193/EB/NIBIB NIH HHS |
| Comments/Corrections | |
Erratum In:
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Phys Med Biol. 2012 Apr 7;57(7):2101 |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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