Segmentation of parotid glands in head and neck CT images using a constrained active shape model with landmark uncertainty

Antong Chen; Jack H. Noble; Kenneth J. Niermann; Matthew A. Deeley; Benoit M. Dawant

doi:10.1117/12.911534

14 February 2012 Segmentation of parotid glands in head and neck CT images using a constrained active shape model with landmark uncertainty

Antong Chen, Jack H. Noble, Kenneth J. Niermann, Matthew A. Deeley, Benoit M. Dawant

Author Affiliations +

Proceedings Volume 8314, Medical Imaging 2012: Image Processing; 83140P (2012) https://doi.org/10.1117/12.911534
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Automatic segmentation of parotid glands in head and neck CT images for IMRT planning has drawn attention in recent years. Although previous approaches have achieved substantial success by reaching high overall volume-wise accuracy, suboptimal segmentations are observed on the interior boundary of the gland where the contrast is poor against the adjacent muscle groups. Herein we propose to use a constrained active shape model with landmark uncertainty to improve the segmentation in this area. Results obtained using this method are compared with results obtained using a regular active shape model through a leave-one-out experiment.

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Antong Chen, Jack H. Noble, Kenneth J. Niermann, Matthew A. Deeley, and Benoit M. Dawant "Segmentation of parotid glands in head and neck CT images using a constrained active shape model with landmark uncertainty", Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83140P (14 February 2012); https://doi.org/10.1117/12.911534

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