Automatic image hanging protocol for chest radiographs in PACS

IEEE Transactions on Information Technology in Biomedicine

Volumn 10, Issue 2, 2006, Pages 302-311

  Luo, Hui ^a   Hao, Wei ^a   Foos, David H ^a   Cornelius, Craig W ^a  

^a EASTMAN KODAK COMPANY   (United States)

Author keywords

Bayesian learning framework; Chest radiography; Hanging protocol; Picture archive and communication system (PACS)

Indexed keywords

BIOLOGICAL MATERIALS; IMAGE ANALYSIS; LEARNING SYSTEMS; RADIOLOGY;

BAYESIAN LEARNING FRAMEWORK; CHEST RADIOGRAPHY; HANGING PROTOCOL; PICTURE ARCHIVE AND COMMUNICATION SYSTEM;

DIAGNOSTIC RADIOGRAPHY;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; COMPUTER ASSISTED DIAGNOSIS; DATA BASE; HOSPITAL INFORMATION SYSTEM; HUMAN; INFORMATION RETRIEVAL; METHODOLOGY; THORAX RADIOGRAPHY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; DATABASE MANAGEMENT SYSTEMS; HUMANS; INFORMATION STORAGE AND RETRIEVAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOGRAPHY, THORACIC; RADIOLOGY INFORMATION SYSTEMS;

EID: 33645718467     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2005.859872     Document Type: Article

References (28)

1. J. M. Boone, G. S. Hurlock, J. A. Seibert, and R. L. Kennedy, "Automated recognition of lateral from PA chest radiographs: Saving seconds in a PACS environment," J. Dig. Imag., vol. 16, no. 4, pp. 345-349, 2003.
2. X. W. Xu, K. Doi, T. Kobayashi, H. MacMahon, and M. L. Giger, "Development of an improved CAD scheme for automated detection of lung nodules in digital chest images," Med. Phys., vol. 24, pp. 1395-1403, 1997.
3. X. W. Xu, S. Katsuragawa, K. Ashizawa, H. MacMahon, and K. Doi, "Analysis of image features of histograms of edge gradient for false positive reduction in lung nodule detection in chest radiographs," Proc. SPIE, pp. 318-326, 3338 1998.
4. S. Katesuragawa, K. Doi, H. MacMaho, L. Monnier-Cholley, J. Morishita, and T. Ishida, "Quantitative analysis of geometric-pattern features of interstitial infiltrates in digital chest radiographs," J. Dig. Imag., vol. 9, pp. 137-144, 1996.
5. T. Ishida, S. Katsuragawa, K. Ashizawa, H. MacMahon, and K. Doi, "Application of artificial neural network for quantitative analysis of image data in chest radiographs for detection of interstitial lung disease," J. Dig. Imag., vol. 11, pp. 182-192, 1998.
6. S. G. Armato, M. L. Giger, and H. MacMahon, "Automated lung segmentation in digitized postero-anterior chest radiographs," Acad. Radiol., vol. 5, pp. 245-255, 1998.
7. F. M. Carrascal, J. M. Carreira, M. Souto, P. G. Tahoces, L. Gomes, and J. J. Vidal, "Automatic calculation of total lung capacity from automatically traced lung boundaries in postero-anterior and lateral digital chest radiographs," Med. Phys., vol. 25, pp. 1118-1131, 1998.
8. E. Pieka and H. K. Huang, "Orientation correction for chest images," J. Dig. Imag., vol. 5, no. 3, pp. 185-189, 1992.
9. J. M. Boone, S. Seshagiri, and R. M. Steiner, "Recognition of chest radiograph orientation for picture archiving and communication systems display using neural networks," J. Dig. Imag., vol. 5, no. 3, pp. 190-193, 1992.
10. M. G. Evanoff and K. M. McNeill, "Automatically determining the orientation of chest images," Proc. SPIE, vol. 3035, pp. 299-308, 1997.
11. H. Arimura, S. Katsuragawa, Q. Li, T. Isguda, and K. Doi, "Development of a computerized method for identifying the postero-anterior and lateral views of chest radiographs by use of a template matching technique," Med. Phys., vol. 29, no. 7, pp. 308-315, 2002.
12. T. M. Lehmann, O. Guild, D. Keysers, H. Schubert, M. Kohnen, and B. B. Wein, "Determining the view of chest radiographs," J. Dig. Imag., vol. 16, no. 3, pp. 281-291, 2003.
13. A. K. Jain and A. Vailaya, "Image retrieval using color and shape," Pattern Recognit., vol. 29, pp. 1233-1244, 1996.
14. W. Ma and H. Zhang, "Content-based image indexing and retrieval," The Handbook of Multimedia Computing, B. Furht, Ed., Boca Raton, FL: CRC, 1998.
15. A. Vailaya, H. Zhang, and A. Jain, "Automatic image orientation detection," in IEEE Int. Conf. Image Proc., vol. 2, 1999, pp. 600-604.
16. Y. Wang and H. Zhang, "Detecting image orientation based on low-level visual content," Comput. Vis. Image Understand., vol. 93, pp. 328-346, 2004.
17. R. Brunelli and T. Poggio, "Face recognition: Features versus templates," IEEE Trans. Pattern Anal. Mach. Intell., vol. 15, no. 10, pp. 1042-1052, Oct. 1993.
18. A. Yuille, P. Hallinan, and D. Cohen, "Feature extraction from faces using deformable templates," Int. J. Comput. Vis., vol. 8, no. 2, pp. 99-111, 1992.
19. M. Turk and A. Pentland, "Eigenfaces for recognition," J. Cogn. Neurosci., vol. 3, no. 1, pp. 71-86, 1991.
20. X. Wang and H. Luo, "An automated and exam-type independent algorithm for the segmentation and extraction of foreground, background, and anatomy regions in digital radiographic images," Proc. SPIE Med. Imag., vol. 5370, no. 24, pp. 1427-1434, 2004.
21. B. S. Morse, S. M. Pizer, and A. Liu, "Multiscale medial analysis of medical images," Image Vis. Comput., vol. 12, no. 6, pp. 327-338, 1994.
22. M. Xu, "The multiscale medial properties of interfering image structures," Pattern Recognit. Lett., vol. 25, pp. 21-34, 2004.
23. H. Blum, "A transformation for extracting new descriptors of shape," in Models for Perception of Speech and Vision Forms, W. Wathen-Dunn, Ed. Cambridge, MA: MIT Press, 1967, pp. 362-380.
24. H. Blum and R. N. Nagel, "Shape description using weighted symmetric axis features," Pattern Recognit., vol. 10, pp. 167-180, 1978.
25. A. Hyvärinen, "Fast and robust fixed-point algorithms for independent component analysis," IEEE Trans. Neural Netw., vol. 10, no. 3, pp. 626-634, May. 1999.
26. A. Dempster, N. Laird, and D. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. R. Statist. Soc. B, vol. 39, no. 1, pp. 1-38, 1976.
27. D. Rumelhart and J. McClelland, Parallel Distributed Processing. Cambridge, MA: MIT Press, 1986, vol. 1.
28. K. K. Sung and T. Poggio, "Example-based learning for view-based human face detection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 1, pp. 39-51, Jan. 1998.