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Efficient 3D medical image segmentation algorithm over a secured multimedia network

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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.

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Author information

Authors and Affiliations

  1. Faculty of Science and IT, Al-Zaytoonah University of Jordan, Amman, Jordan

    Shadi Al-Zu’bi & Bilal Hawashin

  2. Computer Science Department, The Hashemite University, Zarqa, Jordan

    Ala Mughaid

  3. Liverpool John Moores University, Liverpool, UK

    Thar Baker

Authors
  1. Shadi Al-Zu’bi
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  2. Bilal Hawashin
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  3. Ala Mughaid
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  4. Thar Baker
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Correspondence to Shadi Al-Zu’bi.

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Abbreviations

Abbreviations

2D :

2 Dimensional

3D :

3 Dimensional

MIP :

Medical Image Processing

HMM :

Hidden Markov Models

CAD :

Computer Added Diagnosis

AES :

Advanced Encryption Standard

OOI :

Object Of Interest

ROI :

Region Of Interest

GPU :

Graphical Processing Unit

CPU :

Central Processing Unit

MINets :

Multimedia Information Networks

CNN :

Convolutional Neural Network

PET :

Positron Emission Tomography

CT :

Computed Tomography

MRI :

Magnetic Resonance Imaging

IEC :

The International Electrotechnical Commission

NEMA :

National Electrical Manufacturer Association

MRA :

Multi-Resolution Analysis

DICOM :

Digital Imaging and COmmunications

TLS :

Transport Layer Security

CIRS :

Computerized Imaging Reference Systems

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Al-Zu’bi, S., Hawashin, B., Mughaid, A. et al. Efficient 3D medical image segmentation algorithm over a secured multimedia network. Multimed Tools Appl 80, 16887–16905 (2021). https://doi.org/10.1007/s11042-020-09160-6

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  • DOI: https://doi.org/10.1007/s11042-020-09160-6

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