Abstract
Medical image annotation is playing an increasingly important role in clinical diagnosis and medical research. Existing medical image annotation is faced with many demands and challenges. (1) The emergence and sharp increasing speed of multi-dimensional medical images. (2) Image annotation includes not only text annotation, but also graphical annotation, clinical diagnostic information and image content features information. (3) Uneven distribution of medical resources, which makes difficult to aggregate group intelligence from a much larger scale of distributed experts. Most of the present study is texted based within hospitals on single images annotation. It is difficult to organize and manage unstructured medical image annotation and collaborative sharing information. This paper dedicated to the research on collaborative web-based multi-dimensional medical image annotation and retrieval in order to address these problems, overcome the shortcoming of traditional thin client and facilitate medical experts in different locations to exchange views and comments,. It proposed (1) a system architecture that provides authoring, storing, querying, and exchanging of annotations, and supports web-based collaboration. (2) 2D multi-frame and 3D medical image collaborative annotation data model. (3) Collaborative annotation mechanisms.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Shibata T, Suzuki M, Kato T (2004) 3D retrieval system based on cognitive level. In: Proceedings of the 2004 International conference on cyber worlds IEEE
Wang F, Rabsch C, Liu P (2008) Native web browser enabled SVG-based collaborative multimedia annotation for medical images. In: proceedings of the IEEE 24th international conference on data engineering, ICDE 2008, April, pp 1219–1228
Rubin DL, Rodriguez C, Shah P, Beaulieu C (2008) Ipad: semantic annotation and markup of radiological images, AMIA annu symposium proceedings, pp 626–630
Kman P, Friesen WV (1978) Facial action coding system. Consulting Psychologists Press, Palo Alto
Lowe DG (1999) Object recognition from local scale-invariant features. In: Proceedings of the 7th international conference on computer vision, Greece, pp 1150–1157
Lowe DG (2004) Distinctive image features from scale-invariant key points. Int J Comput Vision 60(2):91–110
Zhao H (2007) Research on image registration algorithm based on point features. Shangdong University, Shangdong (in Chinese)
David G, Lowe (2004) Distinctive image features from scale-invariant key points. Int J Comput Vision 60(2):91–110
Mougiakakou SG, Valavanis IK, Mouravliansky NA, Nikita KS, Nikita A (2009) Diagnosis: A telematics-enabled system for medical image archiving, management, and diagnosis assistance. IEEE Trans Instrum Meas 58(7):2113–2120
Alberola C, Cárdenes R, Martín v, Martín M, Rodríguez-Florido M, Ruiz-Alzola J(2000) Disnei: A collaborative environment for medical images analysis and visualization. In medical image computing and computer-assisted intervention, 3rd international conference, Pittsburgh
J. Chun and J. Son, “A CORBA-based telemedicine system for medical image analysis and modeling”, In the 14th IEEE symposium on computer-based medical systems, 2002, pp. 53–58
Papazoglou MP, Traverso P, Dustdar S, Leymann F (2003) Service-oriented computing. Commun ACM 46:25–28
Newcomer E, Lomow G (2004) Understanding SOA with web services (independent technology guides). Addison-wesley professional
Oreilly T (2007) What is web 2.0: design patterns and business models for the next generation of software. SSRN library
Anderson v (2007) What is web 2.0? ideas, technologies and implications for education. JISC Technology and Standards Watch
Acknowledgments
This work was funded by National Science and Technology Major Research Plan of China (grant number 2010ZX01042-002-001) and State Key Laboratory of Software Development Environment (grant number SKLSDE-2010ZX-08). The authors would also like to appreciate all those who took part in the groups and experiments.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yu, G., Ma, D., Shen, H., Huang, Y. (2013). Web-Based Multi-Dimensional Medical Image Collaborative Annotation System. In: Lu, W., Cai, G., Liu, W., Xing, W. (eds) Proceedings of the 2012 International Conference on Information Technology and Software Engineering. Lecture Notes in Electrical Engineering, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34531-9_54
Download citation
DOI: https://doi.org/10.1007/978-3-642-34531-9_54
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34530-2
Online ISBN: 978-3-642-34531-9
eBook Packages: EngineeringEngineering (R0)