|1/2008 - 10|
Ontology-Based Knowledge Organization for the Radiograph Images SegmentationMATEI, O.
|Click to see author's profile on SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (1,103 KB) | Citation | Downloads: 796 | Views: 3,188|
normalization, onotologies, radiographs
medical(12), chest(12), segmentation(8), radiographs(8), lung(8), digital(7), physics(6), analysis(6), imaging(5), feature(4)
Blue keywords are present in both the references section and the paper title.
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.
|References|||||Cited By «-- Click to see who has cited this paper|
| 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 221] [SCOPUS Times Cited 359]
 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 81] [SCOPUS Times Cited 121]
 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 89] [SCOPUS Times Cited 92]
 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]
Web of Science® Citations for all references: 391 TCR
SCOPUS® Citations for all references: 572 TCR
Web of Science® Average Citations per reference: 20 ACR
SCOPUS® Average Citations per reference: 29 ACR
TCR = Total Citations for References / ACR = Average Citations per Reference
We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more
Citations for references updated on 2018-03-14 01:50 in 21 seconds.
Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.