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Landmarking and Feature Localization in Spine X-rays
Acknowledgments The authors acknowledge the very helpful ideas, examples, criticism, and code that is continuing to be provided by Dr. Hemant Tagare of Yale University in the area of using deformable templates to find structures in x-ray images. We also acknowledge the work of Matthew Freedman, M.D. and Dr. Ben Lo of Georgetown University in providing significant biomedical and quantitative data from 600 digitized x-ray images for the continuing research into developing effective image processing techniques for automated image analysis for biomedical applications. Finally, we are grateful to David Blum and Joe Fitzgerald of the National Library of Medicine Audiovisual Program Development Branch for the anatomical artwork used in Figure 3. References 1. Long LR, Pillemer SR, Lawrence RC, Goh G-H, Neve L, Thoma GR. World Wide Web platform-independent access to biomedical text/image databases. 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Automated localization and identification of lower spinal anatomy in magnetic resonance images. Computers and Biomedical Research, vol. 24, 1991, 99-117. 11. Cootes TF, Taylor CJ. Statistical models of appearance for computer vision. Wolfson Image Analysis Unit, Imaging Science and Biomedical Engineering, University of Manchester, September 13, 1999. Draft report, available at http://www.wiau.man.ac.uk. 12. Smyth PP, Taylor CJ, Adams JE. Vertebral shape: automatic measurements with active shape models. Radiology, May 1999, vol. 211, no. 2, pp. 571-578. 13. Gardner JC, Heyano SL, Yaffe LG, von Ingersleben G, Chesnut CH III. A semi-automated computerized system for fracture assessment of spinal x-ray films. Proceedings of SPIE Medical Imaging 1996: Image Processing, SPIE vol. 2710, February 12-15, 1996, Newport Beach, CA, pp. 996-1008. 14. Gardner JC, Yaffe LG, Johansen JM, von Ingersleben G, Chesnut CH III. Problems with six point vertebral morphometry. 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Proceedings of SPIE Medical Imaging 1998: Image Processing, SPIE vol. 3338, San Diego, CA, February 23-26, 1998, pp. 1036-1046. 19. Long LR, Thoma GR. Use of shape models to search digitized spine x-rays. Proceedings of IEEE Computer Based Medical Systems 2000, Houston, TX, June 23-24, 2000, pp. 255-260. 20. Long LR, Thoma GR. Segmentation and image navigation in digitized spine x-rays. Proceedings of SPIE Medical Imaging 2000: Image Processing. Vol. 3979, San Diego, CA, February 12-18, 2000, pp. 169-179. 21. Sari-Sarraf H, Mitra S, Zamora G, Tezmol A. Customized active shape models for segmentation of cervical and lumbar spine vertebrae, Texas Tech University College of Electrical Engineering technical report, available at http://www.cvial.ttu.edu/~sarraf 22. Zamora G, Sari-Sarraf H, Mitra S. Estimation of orientation of cervical vertebrae for segmentation with active shape models. Proceedings of SPIE Medical Imaging 2001: Image Processing, San Diego, CA, February 17-23, 2001. 23. Stanley RJ, Long R. A radius of curvature approach to cervical spine vertebra image analysis. Proceedings of the 38th Annual Rocky Mountain Bioengineering Symposium, Copper Mountain, Colorado, April 20-22, 2001. 24. Plan and operation of the second National Health and Nutrition Examination Survey, 1976-1980, DHHS Pub. No. (PHS) 81-1317, Vital and Health Statistics Series 1, No. 15, Public Health Service, Stock Number 017-022-00752-5, U.S. Government Printing Office, Washington, DC 20402. 25. National Health and Nutrition Examination Survey, 1976-80 (NHANES II), Public Use Data Tape Documentation, Physician's Examination, Tape Number 5302, National Center for Health Statistics, Hyattsville, MD. 26. Chuang K-S, Liu BJ, Huang HK, Yonekawa H, Sankaran A. Noise contnet analysis in clinical digital images. Radiographics, vol. 14, no. 2, March 1994, pp. 397-405. 27. Chuang K-S, Huang HK. Assessment of noise in a digital image using the join-count statistic and the Moran test. 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Long LR, Pillemer S, Goh G-H, Berman LE, Neve L, Thoma GR, Premkumar A, Ostchega Y, Lawrence R, Altman RD, Lane NE, Scott WW, Jr. A digital atlas for spinal x-rays. Proceedings of SPIE Medical Imaging 1997: PACS Design and Evaluation: Engineering and Clinical Issues, SPIE vol. 3035, pp. 586-594, Newport Beach, CA, February 22-28, 1997. 33. Liang Q, Wendelhag I, Wikstrand J, Bustavsson. A multiscale dynamic programming procedure for boundary detection in ultrasonic artery images. IEEE Transactions on Medical Imaging, vol. 19, no. 2, February 2000, pp.127-142. 34. Mignotte M, Meunier J. A multiscale optimization approach for the dynamic contour-based boundary detection issue. Computerized Medical Imaging and Graphics, vol. 25, no. 3, 2001, pp. 265-275. 35. Long LR, Thoma GR. Identification and classification of spine vertebrae by automated methods. Proceedings of SPIE Medical Imaging 2001: Image Processing, San Diego, CA, February 17-23, 2001.120 36. MPEG-7 Context, Objectives and Technical Roadmap. International Organisation for Standardisation, July 1999, Vancouver. http://www.darmstadi.emd.de/mobile/MPEG7/Documents/W2861.htm 37. MPEG-7 Applications Document v.10. International Organisation for Standardisation, January 2001, Pisa. http://www.darmstadt.gmd.de/mobile/MPEG7/Documents/W3934.htm 38. Overview of the MPEG-7 standard. International Organisation for Standarisation, March 2001, Singapore. http://www.cselt.stet.it/mpeg/standards/mpeg-7/mpeg-7.htm
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