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Ontology-Based Knowledge Organization for the Radiograph Images SegmentationMATEI, O.
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normalization, onotologies, radiographs
medical(12), chest(12), segmentation(8), radiographs(8), lung(8), digital(7), physics(6), analysis(6), imaging(5), feature(4)
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About this article
Date of Publication: 2008-04-02
Volume 8, Issue 1, Year 2008, On page(s): 56 - 61
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2008.01010
Web of Science Accession Number: 000259903500010
SCOPUS ID: 70349189190
The quantity of thoracic radiographies in the medical field is ever growing. An automated system for segmenting the images would help doctors enormously. Some approaches are knowledge-based; therefore we propose here an ontology for this purpose. Thus it is machine oriented, rather than human-oriented. That is all the structures visible on a thoracic image are described from a technical point of view.
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| Nci ontology, [Online] Available: Temporary on-line reference link removed - see the PDF document
 Galen ontology, [Online] Available: Temporary on-line reference link removed - see the PDF document
 S. G. Armato and H. Giger, M. L.and MacMahon, "Automated lung segmentation in digitized postero-anterior chest radiographs", Academic Radiology, (4):245-255, 1998. [PubMed]
 M. S. Brown, L.S. Wilson, B.D. Doust, R.W. Gill, and C. Sun., "Knowledgebased method for segmentation and analysis of lung boundaries in chest x-ray images", Computerized Medical Imaging and Graphics", 22:463-477, 1998. [PubMed]
 J. J. Cimino, Hricsak G., Johnson S. B., and Clayton P. D., "Designing an introspective multipurpose controlled medical vocabulary", In Proc 13th AnnuSymp Comput Appl Med Care, pp. 513-517, 1989. [PubMed]
 J. Duryea and J.M. Boone, "A fully automatic algorithm for the segmentation of lung fields in digital chest radiographic images", Medical Physics, 2(22):183-191, 1995. [PubMed]
 B. van Ginneken, A. F. Frangi, J. J. Staal, B. M. ter Haar Romeny, and M. A. Viergever, "Active shape model segmentation with optimal features", IEEE Transactions on Medical Imaging, 21(8):924-933, 2002.
[CrossRef] [Web of Science Times Cited 201] [SCOPUS Times Cited 343]
 B. van Ginneken, Haar Romeny B. M. ter Katsuragawa, S., K. Doi, and M. A. Viergever, "Automatic detection of abnormalities in chest radiographs using local texture analysis", IEEE Transactions on Medical Imaging, 21(2):139-149, 2002.
[CrossRef] [Web of Science Times Cited 76]
 H. Gu, M. Halper, J. Geller, and Y. Perl, "Benefits of an object-oriented database representation for controlled medical terminologies", J Am Med Inform Assoc, (6):283303, 1999. [PubMed]
 L. Li, Y. Zheng, M. Kallergi, and R. A. Clark, "Improved method for automatic identification of lung regions on chest radiographs", Academic Radiology, 7(8):629-638, 2001. [PubMed]
 M. Loog and B. van Ginneken, "Supervised segmentation by iterated contextual pixel classification", In In Proceedings 16th International Conference on Pattern Recognition, pages 925-928, 2002. [PubMed]
 M. F. McNitt-Gray, H. K. Huang, and J. W. Sayre, "Feature selection in the pattern classification problem of digital chest radiograph segmentation", IEEE Transactions on Medical Imaging, 14(3):537- 547, 1995.
[CrossRef] [Web of Science Times Cited 87] [SCOPUS Times Cited 89]
 N. Nakamori, K. Doi, V. Sabeti, and H. MacMahon, "Image feature analysis and computer-aided diagnosis in digital radiography: automated analysis of sizes of heart and lung in chest images", Medical Physics, 17(3):342-350, 1990. [PubMed]
 E. Pietka, "Lung segmentation in digital chest radiographs", Journal of Digital Imaging, 2:79-84, 1994.
 C. Rosse, J. L. Mejino, B. R. Modayur, R. Jakobovits, K. P. Hinshaw, and J. F. Brinkley, "Motivation and organizational principles for anatomical knowledge representation: the digital anatomist symbolic knowledge base", J Am Med Inform Assoc, (5):17-40, 1998. [PubMed]
 C. Rosse, L. G. Shapiro, and J. F. Brinkley, "The digital anatomist foundational model: principles for defining and structuring its concept domain", In Proc AMIA Symp, pages 820-824, 1998. [PubMed]
 O. Tsujii, M. T. Freedman, and S. K. Mun, "Automated segmentation of anatomic regions in chest radiographs using an adaptive-sized hybrid neural network", Medical Physics, 25(6):998-1007, 1998. [PubMed]
 N. F. Vittitoe, R. Vargas-Voracek, and C. E. Floyd Jr., "Identification of lung regions in chest radiographs using markov random field modeling", Medical Physics, 25(6):976-985, 1998. [PubMed]
 X. W. Xu and K. Doi, "Image feature analysis for computer-aided diagnosis: accurate determination of ribcage boundary in chest radiographs", Medical Physics, 5(22):617-626, 1995. [PubMed]
 X. W. Xu and K. Doi, "Image feature analysis for computer-aided diagnosis: detection of right and left hemidiaphragm edges and delineation of lung field in chest radiographs", Medical Physics, 9(23):1613-1624, 1996. [PubMed]
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