Mathematical Methods in Intelligent Medical Image Processing

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E3: Mathematical Biology".

Deadline for manuscript submissions: closed (10 February 2025) | Viewed by 431

Special Issue Editors


E-Mail Website
Guest Editor
School of Computer Science and Engineering, Southeast University, Nanjing 211189, China
Interests: medical image reconstruction; processing and analysis; deep learning

E-Mail Website
Guest Editor
Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
Interests: deep learning; medical imaging; sparse representation

Special Issue Information

Dear Colleagues,

The field of intelligent medical image processing has witnessed remarkable advancements. These have largely been driven by the application of sophisticated mathematical methods. This Special Issue, "Mathematical Methods in Intelligent Medical Image Processing", aims to explore the intersection of mathematics and medical imaging to enhance image quality, improve diagnostic accuracy, and facilitate automated analysis.

This Special Issue will cover a broad range of topics, including the following:

  • Mathematical models, statistical methods, and optimization techniques in medical imaging.
  • Machine learning or deep learning techniques tailored for medical imaging applications.
  • Other advanced algorithms for medical image reconstruction, processing, and analysis.

Contributors are invited to present original research, comprehensive reviews, and case studies that demonstrate the practical impact of mathematical methods in real-world medical imaging scenarios. We seek to highlight interdisciplinary collaborations that bridge the gap between theoretical developments and clinical applications, ultimately aiming to improve patient outcomes.

This Special Issue will serve as a valuable resource for researchers, clinicians, and practitioners interested in the latest mathematical approaches in medical image processing. By fostering a deeper understanding of these methods, we hope to inspire further research and innovation in this dynamic and rapidly evolving field.

Dr. Yikun Zhang
Dr. Dianlin Hu
Guest Editors

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Keywords

  • medical image processing
  • artificial intelligence
  • mathematical methods
  • optimization techniques
  • advanced applications

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Published Papers

There is no accepted submissions to this special issue at this moment.
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