MULTI-MODAL INFORMATION RETRIEVAL FOR CONTENT-BASED MEDICAL IMAGE AND VIDEO DATA MINING

Peijiang Yuan, Bo Zhang, Jianmin Li

2009

Abstract

Image based medical diagnosis plays an important role in improving the quality of health-care industry. Content based image retrieval (CBIR) has been successfully implemented in medical fields to help physicians in training and surgery. Many radiological and pathological images and videos are generated by hospitals, universities and medical centers with sophisticated image acquisition devices. Images and Videos that help senior or junior physician to practice medical surgery become more and more popular and easier to access through different ways. To help learn the process of a surgery or even make decisions is one of the main objectives of the content based image and video retrieval system. In this paper, a contented-based multimodal medical video retrieval system (CBMVR) for medical image and video databases is addressed. Some key issues are discussed. A new feature representation method named Artificial Potential Field (APF) is addressed which is specially useful in symmetrical imaging feature extraction. Experimental results show that, with this CBMVR, both the senior and junior physicians can benefit from the mass data of medical images and videos.

References

  1. Bucci, G., S., C., and Domicinis, R. D. (1996). Integrating content-based retrieval in a medical image reference databasez. Computerized Medical Imaging and Graphics, 20(4):231-241.
  2. Cai, W., Feng, D., and Fulton, R. (2001). Content-based retrieval of dynamic pet functional images. IEEE Trans. Inform. Tech. Biomed, 4(2):152-158.
  3. Cord, M., Fournier, J., and Philipp-Foliguet, S. (2003). Exploration and search-by-similarity in cbir. In Proc. of SIBGRAPI 03, Sao Carlos, Brsil.
  4. Khatib, O. and Maitre, J. L. (1978). Dynamic control of. manipulators operating in a complex environment. Proceedings Third International CISM-IFToMM Symposium,September 1978, pages 267-282.
  5. Kim, C. and Vasudev, B. (2005). Spatiotemporal sequence matching for efficient video copy detection. IEEE Trans. on Circuits and Systems for Video Technology, 15(1):127-132.
  6. Liu, Y., Collins, R., and Rothfus, W. (2001). Robust midsagittal plane extraction from normal and pathological 3d neuroradiology images. IEEE Transactions on Medical Imaging, 20(3):175-192.
  7. Muller, H., Michoux, N., Bandon, D., and Geissbuhler, A. (2004). A review of content-based image retrieval systems in medical applications-clinical benefits and future directions. International Journal of Medical Informatics, 73(1):1-23.
  8. Orphanoudakis, S., Chornaki, C., and Kostomanolakis, S. (1994). I2c-a system for the indexing, storage and retrieval of medical images by content. Med Informatics, 19(2):109-122.
  9. Poggio, T. and Bizzi, E. (2004). Generalization in vision and motor control. NATURE, 296:768-774.
  10. Smeulders, A. W. M., Worring, M., Santini, S., Gupta, A., and Jain, R. (2000). Contentbased image retrieval at the end of the early years. IEEE Trans Pattern Anal Machine Intell, 22(12):1349-1380.
  11. Squire, D. M., Muller, A. W., Muller, H., and Raki, J. (1999). Content-based query of image databases-inspirations from text retrieval-inverted files, frequency-based weights and relevance feedback. Proceeding Scandinavian Conference on Image Analysis, Kangerlussuaq, Greenland, pages 143-149.
  12. Tagare, H., Jaffe, C., and Duncan, J. (1997). Medical image databases - a content-based retrieval approach. Journal of the American Medical Informatics Association, 4:184-198.
  13. Taylor, D. M., Tillery, S. I. H., and Schwartz1, A. B. (2002). Direct cortical control of 3d neuroprosthetic devices. SCIENCE, 296:1829-1832.
Download


Paper Citation


in Harvard Style

Yuan P., Zhang B. and Li J. (2009). MULTI-MODAL INFORMATION RETRIEVAL FOR CONTENT-BASED MEDICAL IMAGE AND VIDEO DATA MINING . In Proceedings of the First International Conference on Computer Imaging Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2009) ISBN 978-989-8111-68-5, pages 83-86. DOI: 10.5220/0001774200830086


in Bibtex Style

@conference{imagapp09,
author={Peijiang Yuan and Bo Zhang and Jianmin Li},
title={MULTI-MODAL INFORMATION RETRIEVAL FOR CONTENT-BASED MEDICAL IMAGE AND VIDEO DATA MINING},
booktitle={Proceedings of the First International Conference on Computer Imaging Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2009)},
year={2009},
pages={83-86},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001774200830086},
isbn={978-989-8111-68-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Imaging Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2009)
TI - MULTI-MODAL INFORMATION RETRIEVAL FOR CONTENT-BASED MEDICAL IMAGE AND VIDEO DATA MINING
SN - 978-989-8111-68-5
AU - Yuan P.
AU - Zhang B.
AU - Li J.
PY - 2009
SP - 83
EP - 86
DO - 10.5220/0001774200830086