Deep Learning and Multimodal Feature Fusion for Advanced Medical Imaging Diagnosis
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Machine Learning and Artificial Intelligence in Diagnostics".
Deadline for manuscript submissions: 30 October 2025 | Viewed by 97
Special Issue Editors
2. Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
Interests: deep learning; feature fusion; medical diagnosis; image processing
Interests: deep learning; feature fusion; multimodal; classification
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The integration of deep learning in multimodal feature fusion is emerging as a transformative approach in medical imaging, offering promising opportunities for enhanced diagnostic accuracy, efficiency, and clinical insight. This Special Issue seeks to gather state-of-the-art research that applies artificial intelligence to advance diagnostic imaging across a wide range of clinical applications.
The focus is on innovative methods that combine imaging data such as MRI, CT, PET, and ultrasound with complementary clinical information, including electronic health records, laboratory findings, and patient history. The goal is to promote techniques that leverage the strengths of data-driven models to support early disease detection, precise characterization, and effective decision making.
Topics of interest include, but are not limited to, the following:
- Deep learning-based classification, segmentation, detection, and reconstruction;
- Multimodal feature fusion integrating image-based and non-image-based data;
- Explainable and trustworthy AI for clinical interpretation;
- Transfer learning, few-shot learning, and domain adaptation in medical imaging;
- Dataset benchmarking, reproducibility, and clinical validation studies.
We welcome original research articles, review papers, and case studies that contribute to advancing the field of AI-powered medical diagnostics through deep learning and feature fusion.
Dr. Sarmad Maqsood
Prof. Dr. Rytis Maskeliūnas
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. Diagnostics 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 2600 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
- feature fusion
- medical imaging
- artificial intelligence in healthcare
- diagnostic imaging
- multimodal data integration
- explainable AI
- clinical decision support
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