Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data-Reference-Cited by-同舟云学术

Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data

Published:2017-02 Issue:2 Volume:44 Page:479-496
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Beichel Reinhard R.¹²,Smith Brian J.³,Bauer Christian¹,Ulrich Ethan J.¹⁴,Ahmadvand Payam⁵,Budzevich Mikalai M.⁶,Gillies Robert J.⁶,Goldgof Dmitry⁷,Grkovski Milan⁸,Hamarneh Ghassan⁵,Huang Qiao⁹,Kinahan Paul E.¹⁰,Laymon Charles M.¹¹¹²,Mountz James M.¹²,Muzi John P.¹⁰,Muzi Mark¹⁰,Nehmeh Sadek¹³,Oborski Matthew J.¹¹,Tan Yongqiang⁹,Zhao Binsheng⁹,Sunderland John J.¹⁴,Buatti John M.¹⁵

Affiliation:

1. Department of Electrical and Computer Engineering; The University of Iowa; Iowa City IA USA

2. Department of Internal Medicine; The University of Iowa; Iowa City IA USA

3. Department of Biostatistics; The University of Iowa; Iowa City IA USA

4. Department of Biomedical Engineering; The University of Iowa; Iowa City IA USA

5. School of Computing Science; Simon Fraser University; Burnaby Canada

6. H Lee Moffitt Cancer Center; Tampa FL USA

7. Department of Computer Science and Engineering; University of South Florida; Tampa FL USA

8. Department of Medical Physics; Memorial Sloan Kettering Cancer Center; New York NY USA

9. Department of Radiology; Columbia University Medical Center; New York NY USA

10. Department of Radiology; University of Washington Medical Center; Seattle WA USA

11. Department of Bioengineering; University of Pittsburgh; Pittsburgh PA USA

12. Department of Radiology; University of Pittsburgh; Pittsburgh PA USA

13. National Center for Cancer Care and Research; Doha Qatar

14. Department of Radiology; The University of Iowa; Iowa City IA USA

15. Department of Radiation Oncology; The University of Iowa; Iowa City IA USA

Publisher

Wiley

Subject

General Medicine

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/mp.12041/fullpdf

Reference35 articles.

1. Radiomics in PET: principles and applications;Cook;Clinical and Translational Imaging,2014

2. Radiomics: the process and the challenges;Kumar;Magn Reson Imaging,2012

3. Prognostic value of FDG PET metabolic tumor volume in human papillomavirus-positive stage III and IV oropharyngeal squamous cell carcinoma;Alluri;AJR Am J Roentgenol,2014

4. FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors;Sridhar;AJR Am J Roentgenol,2014

5. 18F-FDG metabolic tumor volume and total glycolytic activity of oral cavity and oropharyngeal squamous cell cancer: adding value to clinical staging;Dibble;J Nucl Med,2012

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