Identifying regions of interest in medical images using self-organizing maps

Journal of Medical Systems

Volumn 36, Issue 5, 2012, Pages 2761-2768

  Teng, Wei Guang ^a,b   Chang, Ping Lin ^c  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^b not available   (Taiwan)

^c IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Computer aided diagnosis; Image segmentation; Region of interest; Self organizing map

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BONE; BRAIN; CEREBELLUM; COLOR; COMPARATIVE STUDY; CONTROLLED STUDY; CYST; DIAGNOSTIC IMAGING; ECHOGRAPHY; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; LIVER; LUNG LOBE; MENINX; NUCLEAR MAGNETIC RESONANCE IMAGING; RADIOGRAPHY; RADIOLOGIST; SELF ORGANIZING MAP; COMPUTER ASSISTED DIAGNOSIS; METHODOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; RADIOGRAPHY; ULTRASONOGRAPHY;

EID: 84867314255     PISSN: 01485598     EISSN: 1573689X     Source Type: Journal    
DOI: 10.1007/s10916-011-9752-8     Document Type: Article

References (22)

1. Jan J. Medical image processing reconstruction and restoration: concepts and methods. CRC Press, November 2005.
2. Vannier MW, Haller JW. Biomedical image segmentation. Proceedings of the 1998 International Conference on Image Processing, vol. 2, pages 20-24, October 1998.
3. Doi, K.; Computer-aided diagnosis in medical imaging historical review, current status and future potential. Comput. Med. Imaging Graph. 31(45):198-211, 2007.
4. Gurcan, M. N.; Boucheron, L. E.; Can, A.; Madabhushi, A.; Rajpoot, N. M.; Yener, B.; Histopathological image analysis: a review. IEEE Rev. Biomed. Eng. 2:147-171, 2009.
5. Akgül, C. B.; Rubin, D. L.; Napel, S.; Beaulieu, C. F.; Greenspan, H.; Acar, B.; Content-based image retrieval in radiology: current status and future directions. J. Digit. Imaging 24(2):208-222, 2011.
6. Lucchese, L.; Mitra, S. K.; Colour image segmentation: a state-of-art survey. Proc. Indian Nat. Sci. Acad (INSA-A) 67(2):207-221, 2001.
7. Pham, D. L.; Xu, C.; Prince, J. L.; Current methods in medical image segmentation. Annu. Rev. Biomed. Eng. 2:315-337, August 2000.
8. Shah-Hosseini, H.; Safabakhsh, R.; Automatic multilevel thresholding for image segmentation by the growing time adaptive self-organizing map. IEEE Trans. Pattern Anal. Mach. Intell. 24(10):1388-1393, October 2002.
9. Gonzalez RC, Woods RE. Digital image processing. 2nd Edition, Prentice Hall, January 2002
10. Jiang Y, Chen KJ, Zhou ZH. SOM-based image segmentation. Proceedings of the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, pages 640-643, May 2003.
11. Ma, F.; Xia, S.; A multiscale approach to automatic medical image segmentation using self-organizing map. J. Comput. Sci. Technol. 13(5):402-409, 1998.
12. Ong, S. H.; Yeo, N. C.; Lee, K. H.; Venkatesh, Y. V.; Cao, D. M.; Segmentation of color images using a two-stage self-organizing network. Image and Vision Computing 20(4):279-289, April 2002.
13. Işcan, Z.; Kurnaz, M. N.; Dokur, Z.; Ölmez, T.; Ultrasound image segmentation by using wavelet transform and self-organizing neural network. Neural Info. Proc.-Lett. Rev. 10(8-9):183-191, August 2006.
14. Kohonen T. Self-organization and associative memory. 3rd Edition. Springer-Verlag, 1989.
15. Chan, T. F.; Vese, L. A.; Active contours without edges. IEEE Trans. Image Process. 10(2):266-277, February 2001.
16. Wasilewski M. Active contours using level sets for medical image segmentation. http://www.postulate.org/
17. Medical, science and nature images: photography and digital imagery by Scott Camazine, http://www.scottcamazine.com/.
18. SRS-X, http://www.radiology.co.uk/srs-x/.
19. Xray2000 Imagebase, http://www.xray2000.co.uk/ibase5/index.htm.
20. Borsotti, M.; Campadelli, P.; Schettini, R.; Quantitative evaluation of color image segmentation results. Pattern Recog. Lett. 19(8):741-747, June 1998.
21. Meas-Yedid, V.; Glory, E.; Morelon, E.; Pinset, Ch, Stamon, G.; Olivo-Marin, J-Ch, Automatic color space selection for biological image segmentation. Proceedings of the 17th International Conference on. Pattern Recognition 3(23-26):514-517, August 2004.
22. Dong, G.; Xie, M.; Color clustering and learning for image segmentation based on neural networks. IEEE Trans. Neural Netw. 16(4):925-936, July 2005.