Progress and Challenges in Biomedical Image Analysis

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

Deadline for manuscript submissions: 30 December 2024 | Viewed by 89

Special Issue Editors


E-Mail Website
Guest Editor
School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK
Interests: cardiac digital twins; medical image analysis; multi-modal AI

E-Mail Website
Guest Editor
School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK
Interests: medical data analysis; robust and interpretable AI; radiomics

Special Issue Information

Dear Colleagues,

We are currently seeing a growing interest in the dynamic and rapidly evolving field of biomedical image analysis, which plays a vital role in a wide range of healthcare applications, ranging from diagnostics to identifying individualized health trends or treatment. With the development and progress that have been made in biomedical imaging technology, biomedical imaging has become an essential tool in daily medical diagnostics. In addition, transformational analytics tools, especially artificial intelligence (AI) techniques and capabilities, are being made more accessible to researchers and healthcare. This has led to medical image analysis becoming more and more important for both research and clinical medicine/healthcare communities. From traditional radiological imaging to cutting-edge techniques, this Special Issue seeks to create a platform for researchers to not only showcase their latest advancements but also share invaluable insights and collectively address challenges in biomedical image analysis through review papers. Beyond individual contributions, this Special Issue aspires to catalyze a transformative impact on digitization (including AI) in healthcare, with a particular focus on personalized medicine. 

By inviting authors to share their expertise and research findings, the initiative aims to shape the future landscape of biomedical image applications. The overarching goal is to create a knowledge-sharing hub that accelerates progress, fostering innovation in biomedical image analysis and ensuring its continued relevance in the broader context of the evolution of healthcare.

Dr. Lei Li
Dr. Zehor Belkhatir
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 submissions that pass pre-check are 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 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

  • foundation models in medical imaging
  • digital twins
  • image-based personalized medicine
  • integration of imaging and non-imaging data (multi-modal analysis)
  • explainable and interpretable AI
  • radiomics analysis
  • image segmentation
  • image registration
  • image classification
  • advances in machine/deep learning (e.g., federated learning)
  • computer-aided diagnosis and surgery

Published Papers

This special issue is now open for submission.
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