Special Issue "Medical Image Analysis: From Small Size Data to Big Data"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: 30 December 2020.

Special Issue Editors

Prof. Sos Agaian
Website
Guest Editor
Computer Science, College of Staten Island, USA
The Graduate Center, City University of New York (CUNY), NY, USA
Interests: big and small data analytics; computational vision and sensing; machine learning and urban computing; multimodal biometric and digital forensics; information processing and fusion; fast algorithms
Dr. Jim Tang
Website
Guest Editor
College of Computing; Michigan Technological University, Michigan, USA
Interests: biomedical image analysis and biomedical imaging, computer aided cancer detection, biometrics, computer vision, and image understanding

Special Issue Information

Dear Colleagues,  

A huge amount of medical image data is being created by different medical imaging devices and creating great demand for more effective algorithms to analyze and process them. Extraction of useful information from these data can bring great benefits for medical diagnosis and treatment. However, owing to the limitations of computing power, research on medical image data analysis and processing was mainly focused on small-size or middle-size image data sets in the past. With the development of GPU technology and certain other parallel computing platforms (i.e., Hadoop), the analysis and processing of big medical image data sets is now becoming a new research direction. This Special Issue will focus on recent advances on medical image processing techniques, especially techniques for big medical image data analysis and processing, and we hope that through this publication, we can push the research of image processing in health applications.

Topics of interest include (but are not limited to):

  • Deep learning for the analysis of big image data;
  • Large learning networks for medical image analysis;
  • 3D medical image analysis;
  • Image analysis techniques including segmentation, registration, quality enhancement, etc.;
  • Image analysis for oncology;
  • High-accuracy computer-aided detection and diagnosis systems with medical imaging.

Prof. Sos Agaian
Dr. Jim Tang
Guest Editors

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. Applied Sciences is an international peer-reviewed open access semimonthly 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 1800 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.

Keywords

  • Deep learning for the analysis of big image data
  • Large learning networks for medical image analysis
  • 3D medical image analysis
  • Image analysis techniques including segmentation, registration, quality enhancement, etc.
  • Image analysis for oncology
  • High-accuracy computer-aided detection and diagnosis systems with medical imaging

Published Papers

This special issue is now open for submission.
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