PET image segmentation using a Gaussian mixture model and Markov random fields-Reference-Cited by-同舟云学术

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PET image segmentation using a Gaussian mixture model and Markov random fields

Published:2015-03-12 Issue:1 Volume:2 Page:
ISSN:2197-7364
Container-title:EJNMMI Physics
language:en
Short-container-title:EJNMMI Phys

Author:

Layer Thomas,Blaickner Matthias,Knäusl Barbara,Georg Dietmar,Neuwirth Johannes,Baum Richard P,Schuchardt Christiane,Wiessalla Stefan,Matz Gerald

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,Instrumentation,Biomedical Engineering,Radiation

Link

http://link.springer.com/content/pdf/10.1186/s40658-015-0110-7.pdf

Reference43 articles.

1. Hamilton CS, Ebert MA. Volumetric uncertainty in radiotherapy. Clin Oncol. 2005; 17:456–64.

2. Greco C, Rosenzweig K, Cascini GL, Tamburrini O. Current status of PET/CT for tumour volume definition in radiotherapy treatment planning for non-small cell lung cancer (NSCLC). Lung Cancer. 2007; 57:125–34.

3. Breen SL, Publicover J, De Silva S, Pond G, Brock K, O’Sullivan B, et al. Intraobserver and interobserver variability in GTV delineation on FDG-PET-CT images of head and neck cancers. Int J Radiat Oncol Biol Phys. 2007; 68:763–70.

4. Morarji K, Fowler A, Vinod SK, Ho Shon I, Laurence JM. Impact of FDG-PET on lung cancer delineation for radiotherapy. J Med Imaging Radiat Oncol. 2012; 56:195–203.

5. Erdi YE, Mawlawi O, Larson SM, Imbriaco M, Yeung H, Finn R, et al. Segmentation of lung lesion volume by adaptive positron emission tomography image thresholding. Cancer. 1997; 80:2505–9.

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