Computer Vision for Medical Image Analysis

Dear Colleagues,

Medical imaging plays a fundamental role in modern healthcare, providing essential insights into disease diagnosis, prognosis, and treatment planning. With the rapid advancement of imaging technologies, from magnetic resonance imaging (MRI) and computed tomography (CT) to ultrasound and positron emission tomography (PET), the volume and complexity of medical image data have grown exponentially. As a result, automated and intelligent image analysis methods have become indispensable for extracting clinically relevant information, improving diagnostic accuracy, and enhancing workflow efficiency.

Computer vision has emerged as a transformative force in medical image analysis, leveraging artificial intelligence (AI) and deep learning techniques to achieve unprecedented levels of performance in segmentation, classification, registration, and anomaly detection. From early-stage disease detection to personalized treatment strategies, the integration of AI-driven computer vision methods is reshaping the landscape of medical diagnostics and decision-making. However, several challenges remain, including the need for robust generalization across diverse patient populations, the interpretability of AI-driven models, and the integration of multi-modal imaging data for comprehensive analysis.

This Special Issue aims to bring together cutting-edge research at the intersection of computer vision and medical image analysis. We invite contributions that address novel methodologies, applications, and theoretical advancements in this domain. Topics of interest include, but are not limited to, the following:

• AI-driven segmentation, classification, and detection in medical imaging;
• Self-supervised and unsupervised learning for medical image analysis;
• Explainability and interpretability of deep learning models in healthcare;
• Multi-modal and multi-scale image analysis;
• Domain adaptation and generalization in medical imaging AI;
• Integration of imaging and non-imaging clinical data;
• Real-time and resource-efficient AI for medical imaging applications;
• Federated learning and privacy-preserving techniques for medical imaging AI;
• Application of generative models in medical image synthesis and augmentation.

Through this Special Issue, we aim to highlight pioneering research that advances the field of medical image analysis and fosters collaboration between computer vision experts and medical professionals. We encourage submissions that not only present technical innovations but also demonstrate their clinical relevance and potential for real-world deployment.

We look forward to receiving high-quality contributions that will shape the future of AI-driven medical image analysis and accelerate the translation of cutting-edge computer vision technologies into clinical practice.

Dr. Rahman Attar
Dr. Le Zhang
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.

• medical image analysis
• computer vision
• artificial intelligence
• deep learning
• machine learning
• federated learning
• self-supervised learning
• multi-modal imaging
• generative models
• healthcare AI
• clinical decision support
• automated diagnosis