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Al-Zu’bi, S, Hawashin, B, Mughaid, A and Baker, T (2020) Efficient 3D Medical Image Segmentation Algorithm over a Secured Multimedia Network. Multimedia Tools and Applications, 80. pp. 16887-16905. ISSN 0942-4962
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Abstract
Image segmentation has proved its importance and plays an important role in various domains such as health systems and satellite-oriented military applications. In this context, accuracy, image quality, and execution time deem to be the major issues to always consider. Although many techniques have been applied, and their experimental results have shown appealing achievements for 2D images in real-time environments, however, there is a lack of works about 3D image segmentation despite its importance in improving segmentation accuracy. Specifically, HMM was used in this domain. However, it suffers from the time complexity, which was updated using different accelerators. As it is important to have efficient 3D image segmentation, we propose in this paper a novel system for partitioning the 3D segmentation process across several distributed machines. The concepts behind distributed multimedia network segmentation were employed to accelerate the segmentation computational time of training Hidden Markov Model (HMMs). Furthermore, a secure transmission has been considered in this distributed environment and various bidirectional multimedia security algorithms have been applied. The contribution of this work lies in providing an efficient and secure algorithm for 3D image segmentation. Through a number of extensive experiments, it was proved that our proposed system is of comparable efficiency to the state of art methods in terms of segmentation accuracy, security and execution time.
| Item Type: | Article |
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| Additional Information: | This is a post-peer-review, pre-copyedit version of an article published in Multimedia Tools and Applications. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11042-020-09160-6 |
| Uncontrolled Keywords: | 0803 Computer Software, 0805 Distributed Computing, 0806 Information Systems, 0801 Artificial Intelligence and Image Processing |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Computer Science & Mathematics |
| Publisher: | Springer (part of Springer Nature) |
| Date Deposited: | 12 Jun 2020 10:23 |
| Last Modified: | 12 Jan 2022 14:30 |
| DOI or ID number: | 10.1007/s11042-020-09160-6 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/13089 |
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