Abstract
This article addresses a multi-query optimization problem for distributed medical image retrieval in mobile wireless networks by exploiting the dependencies in the derivation of a retrieval evaluation plan. To the best of our knowledge, this is the first work investigating batch medical image retrieval (BMIR) processing in a mobile wireless network environment. Four steps are incorporated in our BMIR algorithm. First, when a number of retrieval requests (i.e., m retrieval images and m radii) are simultaneously submitted by users, then a cost-based dynamic retrieval (CDRS) scheduling procedure is invoked to efficiently and effectively identify the correlation among the retrieval spheres (requests) based on a cost model. Next, an index-based image set reduction (ISR) is performed at the execution-node level in parallel. Then, a refinement processing of the candidate images is conducted to get the answers. Finally, at the transmission-node level, the corresponding image fragment (IF) replicas are chosen based on an adaptive multi-resolution (AMR)-based IF replicas selection scheme, and transmitted to the user-node level by a priority-based IF replicas transmission (PIFT) scheme. The experimental results validate the efficiency and effectiveness of the algorithm in minimizing the response time and increasing the parallelism of I/O and CPU.
- M. S. Anbarasi, K. M. Mehata, S. Sandhya, and V. Suganya. 2009. Medical image retrieval from distributed environment. In International Conference on Intelligent Agent and Multi-Agent Systems.Google Scholar
- Android. 2010. Retrieved July 9, 2015 from www.google.com/android.Google Scholar
- S. M. Aziz and M. P. Duc. 2013. Energy efficient image transmission in wireless multimedia sensor networks. IEEE Communications Letters, 17, 6, 1084--1087.Google Scholar
Cross Ref
- C. C. Chang, F. C. Shine, and T. S. Chen. 1999. A new scheme of progressive image transmission based on bit-plane method. In Asia-Pacific Conference on Communications and 4th Optoelectronics and Communications Conference. 2. 892--895.Google Scholar
- C. C. Chang and M. N. Wu. 2003. A color image progressive transmission method by common bit map block truncation coding approach. In International Conference on Communication Technology. 2, 1774--1778.Google Scholar
- C. C. Chang, T. K. Shih, and I. C. Lin. 2002. An efficient progressive image transmission method based on guessing by neighbors. The Visual Computer 18, 341--353.Google Scholar
- R. C. Chang, T. K. Shih, and H. H. Hsu. 2008. A strategic decomposition for adaptive image transmission. Journal of Information Science and Engineering 24, 3, 691--707.Google Scholar
- A. Charisi and V. Megalooikonomou. 2010. Content-based medical image retrieval in peer-to-peer systems. In ACM International Health Informatics Symposium. 724--733. Google Scholar
Digital Library
- J. T. Charles and L. P. Larry. 1992. Image transfer: An end-to-end design. In ACM SIGCOMM. 258--268. Google Scholar
Digital Library
- J. M. Danskin, M. D. Georey, and X. Y. Song. 1995. Fast lossy Internet image transmission. In ACM Multimedia. 321--332. Google Scholar
Digital Library
- T. Deselaers. 2003. Features for Image Retrieval. PhD. dissertation. Aachen, Germany: Rheinisch-Westfalische Technische Hochschule Aachen.Google Scholar
- T. Deselaers, Fire. 2009. Retrieved July 9, 2015 from http://thomas.deselaers.de/fire.Google Scholar
- M. Flickner, H. Sawhney, W. Niblack, and J. Ashley. 1995. Query by image and video content: The QBIC system. Computers 28, 9, 23--31. Google Scholar
Digital Library
- B. J. Frey and D. Dueck. 2007. Clustering by passing messages between data points. Science 315, 972--976.Google Scholar
Cross Ref
- D. H. Gao, D. H. Liu, Y. Q. Feng, et al. 2010. A robust image transmission scheme for wireless channels based on compressive sensing. In International Conference on Intelligent Computing. 334--341. Google Scholar
Digital Library
- H. V. Jagadish, B. C. Ooi, K. L. Tan, C. Yu, and R. Zhang. 2005. iDistance: An adaptive B+-tree based indexing method for nearest neighbor search. ACM Transactions on Database Systems 30, 2, 364--397. Google Scholar
Digital Library
- A. Kementsietsidis, F. Neven, D. Van de Craen, et al. 2008. Scalable multi-query optimization for exploratory queries over federated scientific databases. In Proceedings of the VLDB Endowment. 1, 1, 16--27. Google Scholar
Digital Library
- J. H. Kim and W. J. Song. 1996. Pyramid-structured progressive image transmission using quantization error delivery in transform domains. IEEE Vision, Image and Signal Processing. 143, 132--136.Google Scholar
Cross Ref
- W. C. Le, A. Kementsietsidis, and S. Y. Duan, et al. 2012. Scalable multi-query optimization for SPARQL. In ICDE’12. Google Scholar
Digital Library
- T. Lin and P. Hao. 2005. Compound image compression for real-time computer screen image transmission. IEEE Transactions on Image Processing 14, 8, 993--1005. Google Scholar
Digital Library
- MImage archive. 2010. http://www.ece.ncsu.edu/imaging/Archives/ImageDataBase/Medical/index.html.Google Scholar
- H. Muller, N. Michoux, D. Bandon, and A. Geissbuhler. 2004. A review of content-based image retrieval systems in medical applications—clinical benefits and future directions. International Journal of Medical Informatics 73, 1--23.Google Scholar
Cross Ref
- MySQL. 2010. Retrieved July 9, 2015 from http://www.mysql.com/.Google Scholar
- S. B. Pinar, B. Sebnem, and A. Emre Harmanci. 2011. Robust image transmission over wireless sensor networks. Journal Mobile Networks and Applications Archive 16, 2, 149--170. Google Scholar
Digital Library
- S. Raman, H. Balakrishnan, and M. Srinivasan. 2000. An image transport protocol for the Internet. In ICNP. 209--219. Google Scholar
Digital Library
- P. Roy, S. Seshadri, S. Sudarshan, et al. 2000. Efficient and extensible algorithms for multi query optimization. In SIGMOD 2000. Google Scholar
Digital Library
- Y. Rui, T. S. Huang, and S. F. Chang. 1999. Image retrieval: current techniques, promising directions and open issues. Journal of Visual Communication and Image Representation 10, 39--62. Google Scholar
Digital Library
- V. G. Ruiz, J. J. Fernández, and I. García. 2001. Image compression for progressive transmission. In Proceedings of the 19th IASTED International Conference on Applied Informatics: Advances in Computer Applications. 519--524.Google Scholar
- T. K. Sellis. 1988. Multi-query optimization. ACM Transactions on Database Systems 13, 1. Google Scholar
Digital Library
- H. T. Shen, B. C. Ooi, and X. F. Zhou. 2005. Towards effective indexing for very large video sequence database. In SIGMOD 2005. Google Scholar
Digital Library
- C. R. Shyu, C. E. Brodley, A. C. Kak, et al. 1999. ASSERT: A physician-in-the-loop content-based retrieval system for HRCT image databases. Computer Vision and Image Understanding 75, 111--132. Google Scholar
Digital Library
- J. Smith and S. F. Chang. 1996. VisualSEEK: A fully automated content-based image query system. In ACM Multimedia. Google Scholar
Digital Library
- J. Smith and S. F. Chang. 1997. WebSEEK: A content-based image and video search and catalog tool for the Web. IEEE Multimedia.Google Scholar
- Y. Sun and Z. X. Xiong. 2006. Progressive image transmission over space--time coded OFDM-Based MIMO Systems with adaptive modulation. IEEE Transactions on Mobile Computing 5, 8, 1016--1028. Google Scholar
Digital Library
- N. Trigon, Y. Yao, A. Demers, et al. 2005. Multi-query optimization for sensor networks. In Proceedings of the 1st IEEE International Conference on Distributed Computing in Sensor Systems. 307--321. Google Scholar
Digital Library
- K. H. Tzou. 1987. Progressive image transmission: a review and comparison of techniques. Optical Engineering 26, 581--589.Google Scholar
Cross Ref
- Y. Zhuang, Q. Li, and L. Chen. 2008. Multi-query optimization for distributed similarity query processing. In ICDCS’08. 639--646. Google Scholar
Digital Library
- Y. Zhuang, N. Jiang, Z. A. Wu, Q. Li, et al. 2014. Efficient and robust large medical image retrieval in mobile cloud computing environment. Information Sciences 263, 60--86. Google Scholar
Digital Library
Index Terms
Progressive Batch Medical Image Retrieval Processing in Mobile Wireless Networks
Recommendations
Automatic medical image annotation and retrieval
The demand for automatically annotating and retrieving medical images is growing faster than ever. In this paper, we present a novel medical image retrieval method for a special medical image retrieval problem where the images in the retrieval database ...
Multiple transmission optimization of medical images in recourse-constraint mobile telemedicine systems
A concurrent transmission platform for multiple medical images.Transmission performance improvement from a perspective of the batch transmission processing.Cost-aware multiple transmission requests grouping.Adaptive adjustment of the pixel resolutions ...
Content Based Medical Image Retrieval Based on Salient Regions Combined with Deep Learning
AbstractIn traditional text based medical image retrieval system, it is hard to find visually similar images in large medical image database. Content-based image retrieval is developed to retrieve similar images and it is based on visual attributes ...






Comments