Journal of Medical Systems

, Volume 35, Issue 6, pp 1477–1484 | Cite as

Bleeding Detection in Wireless Capsule Endoscopy Based on Probabilistic Neural Network

  • Guobing PanEmail author
  • Guozheng Yan
  • Xiangling Qiu
  • Jiehao Cui
Original Paper


Wireless Capsule Endoscopy (WCE), which allows clinicians to inspect the whole gastrointestinal tract (GI) noninvasively, has bloomed into one of the most efficient technologies to diagnose the bleeding in GI tract. However WCE generates large amount of images in one examination of a patient. It is hard for clinicians to leave continuous time to examine the full WCE images, and this is the main factor limiting the wider application of WCE in clinic. A novel intelligent bleeding detection based on Probabilistic Neural Network (PNN) is proposed in this paper. The features of bleeding region in WCE images distinguishing from non-bleeding region are extracted. A PNN classifier is built to recognize bleeding regions in WCE images. Finally the intelligent bleeding detection method is implemented through programming. The experiments show this method can correctly recognize the bleeding regions in WCE images and clearly mark them out. The sensitivity and specificity on image level are measured as 93.1% and 85.6% respectively.


Wireless capsule endoscopy Gastrointestinal tract Probabilistic neural network Bleeding detection 



This research was supported by the National Hi-Tech Research and Development Program (863) of China (2006AA04Z368) and the National Natural Science Foundation of China (30570485).


  1. 1.
    National digestive diseases information clearinghouse. Bleeding in the digestive tract. Bethesda: National Institutes of Health, 7:1–6, 2004.Google Scholar
  2. 2.
    Eliakim, R., Suissa, A., Yassin, K., Katz, D., and Fischer, D., Wireless capsule video endoscopy compared to barium follow-through and computerised tomography in patients with suspected Crohn’s disease—final report. Dig Liver Dis 36(8):519–522, 2004.CrossRefGoogle Scholar
  3. 3.
    Iddan, G., Meron, G., Glukhovsky, A., and Swain, P., Wireless capsule endoscopy. Nature 405(6785):417–417, 2000.CrossRefGoogle Scholar
  4. 4.
    Swain, P., Iddan, G.J., Meron, G., and Glukhovsky, A., Wireless capsule endoscopy of the small bowel: development, testing, and first human trials. Biomonitoring and Endoscopy Technologies, Amsterdam, Netherlands, SPIE, 4158:19–23, 2001.Google Scholar
  5. 5.
    Sturniolo, G. C., Leo, V. D., Vettorato, M. G., Boni, M. D., Lamboglia, F., Bona, M. D., Bellumat, A., Martines, D., and D’Inca, R., Small bowel exploration by wireless capsule endoscopy: results from 314 procedures. Am. J. Med. 119(4):341–347, 2006.CrossRefGoogle Scholar
  6. 6.
    Kameda, N., Higuchi, K., Shiba, M., Tabuchi, M., Sugimori, S., Yukawa, T., Kadouchi, K., Okazaki, H., Machida, H., Inagawa, M., Wada, T., Tanigawa, T., Yamagami, H., Watanabe, K., Watanabe, T., Tominaga, K., Fujiwara, Y., Oshitani, N., and Arakawa, T., A prospective trial comparing wireless capsule endoscopy and double-balloon enteroscopy in patients with obscure gastrointestinal bleeding. Gastrointest. Endosc. 63(5):AB162–AB162, 2006.CrossRefGoogle Scholar
  7. 7.
    Storch, I. M., Schmelkin, I., Vance, S., and Barkin, J., A double blind placebo controlled study of tegaserod to increase gastric and small bowel transit times with wireless capsule endoscocpy (WCE). Gastrointest. Endosc. 63(5):AB192–AB192, 2006.CrossRefGoogle Scholar
  8. 8.
    Canlas, K. R., Dobozi, B. M., Lin, S., Smith, A. D., Rockey, D. C., Muir, A. J., Agrawal, N. M., Poleski, M. H., Patel, K., and McHutchison, J. G., Using capsule endoscopy to identify GI tract lesions in cirrhotic patients with portal hypertension and chronic anemia. J. Clin. Gastroenterol. 42(7):844–848, 2008.CrossRefGoogle Scholar
  9. 9.
    Chan, F. S., and Chu, K. M., Capsule endoscopy for gastrointestinal bleeding of obscure origin. Asian J. Surg. 31(2):96–99, 2008.CrossRefGoogle Scholar
  10. 10.
    Buscaglia, J. M., Giday, S. A., Kantsevoy, S. V., Clarke, J. O., Magno, P., Yong, E., and Mullin, G. E., Performance characteristics of the suspected blood indicator feature in capsule endoscopy according to indication for study. Clin. Gastroenterol. Hepatol. 6(3):298–301, 2008.CrossRefGoogle Scholar
  11. 11.
    Liangpunsakul, S., Mays, L., and Rex, D. K., Performance of given suspected blood indicator. Am. J. Gastroenterol. 98(12):2676–2678, 2003.CrossRefGoogle Scholar
  12. 12.
    Mackiewicz, M., Fisher, M., and Jamieson, C., Bleeding detection in Wireless Capsule Endoscopy using adaptive colour histogram model and Support Vector Classification. Medical Imaging 2008 Conference, San Diego, CA, SPIE, 6914: R1–R12, 2008.Google Scholar
  13. 13.
    Bourbakis, N., Makrogiannis, S., and Kavraki, D., A neural network-based detection of bleeding in sequences of WCE images. 5th IEEE Symposium on Bioinformatics and Bioengineering, Minneapolis, MN, IEEE Computer Soc, 324–327, 2005.Google Scholar
  14. 14.
    Li, B.P., and Meng, Q.H., Computer aided detection of bleeding in capsule endoscopy images. 2008 Canadian Conference on Electrical and Computer Engineering, Niagara Falls, CANADA, 1875-1878, 2008.Google Scholar
  15. 15.
    Pan, G., Yan, G., Song, X., and Qiu, X., BP neural network classification for bleeding detection in wireless capsule endoscopy. J. Med. Eng. Technol. 33(7):575–581, 2009.CrossRefGoogle Scholar
  16. 16.
    Hwang, S., Oh, J., Cox, J., Tang, S.J., and Tibbals, H.F., Blood detection in wireless capsule endoscopy using expectation maximization clustering. Medical Imaging 2006: Image Processing, San Diego, CA, USA, SPIE, 6144:1–11.Google Scholar
  17. 17.
    Jung, Y.S., Kim, Y.H., Lee, D.H., and Kim, J.H., Active blood detection in a high resolution capsule endoscopy using color spectrum transformation. International Conference on BioMedical Engineering and Informatics, Washington, DC, USA, IEEE, 1:859–862.Google Scholar
  18. 18.
    Spech, T. D., Probabilistic neural network. Neural Netw. 3(1):109–118, 1990.CrossRefGoogle Scholar
  19. 19.
    The Mathworks, Probabilistic Neural Networks. [15, September 2009].
  20. 20.
    Altman, D. G., and Bland, J. M., Diagnostic tests 1: Sensitivity and specificity. BMJ 308(6943):1552, 1994.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Guobing Pan
    • 1
    Email author
  • Guozheng Yan
    • 1
  • Xiangling Qiu
    • 1
  • Jiehao Cui
    • 1
  1. 1.School of Electronics, Information and Electrical EngineeringShanghai JiaoTong UniversityShanghaiPeople’s Republic of China

Personalised recommendations