Special Issue "Deep Learning Advances in Medical Image Analysis"

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Assistive Technologies".

Deadline for manuscript submissions: closed (30 September 2021).

Special Issue Editor

Prof. Dr. Serestina Viriri
E-Mail Website
Guest Editor
School of Mathematics, Statistics and Computer Science, University KwaZulu-Natal, Durban, South Africa
Interests: computer vision; medical imaging; machine learning; deep learning; image analysis; remote sensing; pattern recognition

Special Issue Information

Dear Colleagues,

Technologies is seeking original and unpublished manuscripts for a Special Issue entitled “Deep Learning Advances in Medical Image Analysis”.

Medical image analysis has a long and distinguished history spanning many decades. The evolution of the general field of image analysis largely parallels that of medical image analysis as some of the earliest image analysis techniques were developed in the context of medical applications. With advancements in technology, medical image analysis has been a primary focus of the application of the advanced and emerging artificial-intelligence-related technologies. Machine learning advances, particularly in deep learning, are playing a pivotal role in medical image analysis. There are several new challenges for researchers and medical practitioners as the numerous methods developed are generally inapplicable and unadaptable to all images. Furthermore, there are either remarkable visual similarities or completely diverging dissimilarities among medical images depending on the medical imaging domain, imaging equipment, and imaging condition, making automated analysis in this domain highly challenging. This Special Issue of Technologies aims to publish state-of-the-art research findings on the artificial-intelligence-related advances made in medical image analysis. We are interested in contributions involving a wide a variety of advances in medical image analysis, including, but not limited to, cancer detection, chest/bone X-ray analysis, ultrasound images, coronary artery analysis, skin lesion analysis, abdominal organ analysis, lung pulmonary nodule detection, tuberculosis diagnosis, COVID-19 detection, and retinal image analysis.

This Special Issue aims to cover all aspects of medical image analysis. Topics of interest include, but are not limited to, the following:

  • Enhancement
  • Segmentation
  • Feature extraction
  • Content-based retrieval
  • Classification
  • Visualization

Prof. Dr. Serestina Viriri
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Technologies is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Medical image analysis
  • Deep learning
  • Machine learning
  • Medical imaging

Published Papers

There is no accepted submissions to this special issue at this moment.
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