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Deep Learning for Biomedical Image Analysis: Recent Advances and Future Trends

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

Deadline for manuscript submissions: 20 November 2025 | Viewed by 85

Special Issue Editors


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Guest Editor
Tuxtla Gutiérrez Institute of Technology, Tuxtla Gutierrez 29020, Mexico
Interests: artificial intelligence; computer vision; specialized computing architectures for real-time image processing

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Guest Editor
Department of Physics and Chemistry, University of Palermo, 90133 Palermo, Italy
Interests: medical imaging; artificial intelligence; pattern recognition; machine learning; applied physics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Deep learning has revolutionized biomedical image analysis, enabling significant advancements in disease diagnosis, treatment planning, and drug discovery. This Special Issue aims to showcase cutting-edge research and novel applications of deep learning techniques in biomedical imaging. We invite original research articles, comprehensive reviews, and insightful perspectives exploring the following topics:

  • Novel deep learning architectures: CNNs, RNNs, GANs, transformers, and hybrid models tailored for biomedical image analysis.
  • Applications including diverse imaging modalities, such as microscopy, endoscopy, radiology (X-ray, CT, MRI), ultrasound, and multimodal imaging.
  • Specific clinical challenges: Cancer detection, neurological disorders, cardiovascular diseases, ophthalmology, and infectious disease diagnosis.
  • Methodological advancements: Explainable AI, uncertainty quantification, federated learning, and data augmentation strategies for biomedical images.
  • Emerging trends: Integration of deep learning with other technologies, ethical considerations, and the development of robust and clinically translatable solutions.

This Special Issue will provide a platform for researchers to disseminate their latest findings and foster collaborations, ultimately contributing to advancing deep learning for improved healthcare outcomes.

Dr. Madaín Pérez‐Patricio
Prof. Dr. Donato Cascio
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. 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 2400 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

  • artificial intelligence
  • computer vision
  • biomedical imaging
  • disease diagnosis

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Published Papers

This special issue is now open for submission.
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