Special Issue on Biomedical Imaging Technologies for IoT Devices Using Edge Computing

Submission Deadline: Jan. 10, 2020

Please click the link to know more about Manuscript Preparation: http://www.acmath.org/submission

Please download to know all details of the Special Issue

Special Issue Flyer (PDF)
  • Lead Guest Editor
    • Mohamed Adel Hammad
      Information Technology Department, Faculty of Computers and Information, Menoufia University, Menoufia, Egypt
  • Guest Editor
    Guest Editors play a significant role in a special issue. They maintain the quality of published research and enhance the special issue’s impact. If you would like to be a Guest Editor or recommend a colleague as a Guest Editor of this special issue, please Click here to complete the Guest Editor application.
    • Ibrahim Elgendy
      School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Hei Longjiang, China
    • Hamada Zahera
      Data Science Group, University of Paderborn, Paderborn, Germany
    • Mostafa Elgendy
      Department of Electrical Engineering and Information Systems, University of Pannonia, Pannonia, Hungary
    • Amgad Mohammed
      DeustoTech, Deusto University, Bilbao, Spain
    • Mahmoud Eissa
      Computational Mathematics Department, Faculty of Science, Menoufia University, Menoufia, Egypt
  • Introduction

    Nowadays, with the considerable growth of the Internet-of-Things (IoT) devices ranging from wearables, smartphones, and virtual reality facilities to internet-connected sensors, the field of medical expects to gain a large benefit. Especially, the biomedical imaging technologies utilize either x-rays (CT scans), sound (ultrasound), magnetism (MRI), radioactive pharmaceuticals (nuclear medicine: SPECT, PET) or light (endoscopy, OCT) to acquire and communicate unprecedented data which used to assess the current condition of an organ or tissue as well as monitor the patient over time for diagnostic and treatment evaluation. However, these devices are still resource-constrained with limited computation power and energy where the collected data becomes increasingly complex and needs to be analyzed quickly. Edge computing is becoming more prominent solution in biomedical imaging technologies to overcome these limitations and introduce more internet of things (IoT) devices for analytics as well as facilitate connectivity, data transfer, and query able local database. As the number of analytics solutions and IoT devices introduced into healthcare networks grows, this special issue aims to explore more advanced ways of handling data to ensure clinicians receive data in a real time.

    Aims and Scope:

    1. Machine learning/deep learning for biomedical imaging
    2. Biomedical imaging and pattern recognition
    3. Biomedical Signal and Image Processing of IoT
    4. Biomedical data mining, data modelling and big-data analytics
    5. IoT architecture, implementation and medical application using edge computing
    6. New Edge computing architecture for biomedical imaging

  • Guidelines for Submission

    Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.

    Papers should be formatted according to the guidelines for authors (see: http://www.acmath.org/submission). By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at http://www.sciencepublishinggroup.com/login. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.