Special Issue "Advances in Machine Learning for Biomedical Signal and Image Processing"

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: 28 February 2022.

Special Issue Editor

Prof. Dr. Lotfi Chaari
E-Mail Website
Guest Editor
Institut de Recherche en Informatique de Toulouse, Institut National Polytechnique, Toulouse, France
Interests: machine learning; artificial intelligence; medical imaging; remote sensing; inverse problems

Special Issue Information

Dear Colleagues,

Machine learning (ML) is today being widely used as a solution to learn from data how to solve problems difficult to model in an analytical way. Due to the democratization of efficient and user-friendly computational facilities, many applications are taking advantage from ML tools. In this sense, the biomedical signal and image processing community is facing a great challenge and opportunity to integrate ML tools in applications such as diagnosis aid, reconstruction, restoration, and data analysis. From diagnosis to therapy, ML for biomedical signal and image processing is a hot research topic with high potential at both methodological and applicative levels.

The motivation behind this proposal lies in the emergence of the use of ML in the biomedical field. This Special Issue will contribute to outline recent advances in different applications handling biomedical signals and images with ML tools. The goal is to point out how ML and deep learning methods can solve various problems in biomedical signal and image processing such as segmentation, super-resolution, reconstruction, detection, etc.

The goal of this Special Issue is to bring together a number of recent methodological and applied advances in machine learning for biomedical data that are of particular interest to the signal and image processing community in view of their challenges and opportunities.

Indeed, the interest of both the machine learning and the medical imaging specialized research communities in the topic is clearly reflected by the organization of special sessions in conferences like ISBI 2020, WCCI 2020, BIOSTEC 2021, EUSIPCO 2021, and ICDHT 2021.

We request contributions presenting methodological and/or applied advances in any application handling biomedical signals or images using ML approaches. Scientifically-founded innovative and speculative research lines are welcome for proposal and evaluation.

Prof. Dr. Lotfi Chaari
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. Journal of Imaging is an international peer-reviewed open access monthly 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 1600 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

  • machine learning
  • deep learning
  • medical imaging
  • biomedical signal

Published Papers

This special issue is now open for submission.
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