Special Issue on Practical Applications of Deep Learning Methods in Medical Image Analysis

Submission Deadline: Aug. 10, 2020

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

Please download to know all details of the Special Issue

Special Issue Flyer (PDF)
  • Lead Guest Editor
    • Dimitrij Shulkin
      RobotDreams, Hamburg, Germany
  • 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.
    • Samuel Abramov
      Robot Dreams, Hamburg, Germany
    • Ivan Panshin
      Promobot, Warminster, Pennsylvania, USA
  • Introduction

    Modern techniques in Deep Learning help to find, identify, classify, and quantify patterns in medical images outperforming medical experts. Deep Learning is rapidly becoming a state of the art, leading to increased productivity in a variety of medical applications. There are many interesting challenges like Kaggle challenges or Grand Challenges in Biomedical Image Analysis that accelerate this development. It is time to take stock of the interim results in terms of practical applications of Deep Learning in the medical field.
    Aims and Scope:
    1. Tissue Segmentation
    2. Cancer Detection
    3. Digital Pathology
    4. Image Recognition
    5. Computational Diagnostics
    6. Classification

  • 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 Submissions must be previously unpublished and may not be under consideration elsewhere.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.ajcst.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.