Mathematical Modeling of Multi-Modal Semantic Enhancement and Analysis in Medical Imaging
A Special Issue of Mathematics (ISSN 2227-7390) belonging to the section "E3: Mathematical Biology".
Deadline for manuscript submissions: 20 November 2026 | Viewed by 238
Editors
Interests: machine learning; medical image analysis; computer vision
Special Issues, Collections and Topics in MDPI journals
Interests: medical image analysis; biomedical image segmentation; weakly supervised learning; person re-identification; visible-thermal cross-modal learning; human anomaly detection; deep representation learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue, "Mathematical Modeling of Multi-Modal Semantic Enhancement and Analysis in Medical Imaging" explores the integration of diverse data streams—such as MRI, CT, clinical text, and omics—to transcend the limitations of single-modality analysis. As healthcare enters a data-rich era, the core challenge lies in fusing heterogeneous information while preserving critical clinical semantics.
We invite contributions that develop rigorous mathematical frameworks for:
Feature Fusion & Alignment: Novel algorithms for cross-modal registration and representation learning that bridge the gap between imaging and non-imaging data.
Semantic Enhancement: Utilizing transformers, vision-language models (VLMs), and knowledge graphs to map raw pixels to high-level medical concepts.
Robustness & Interpretability: Addressing data scarcity and model "black-box" issues through self-supervised learning and clinically-grounded validation.
Medical Image Analysis & Interpretation: Advanced mathematical and computational approaches for segmentation, lesion detection, disease classification, and longitudinal analysis, with an emphasis on integrating multi-modal data to enhance diagnostic and prognostic performance.
By focusing on the mathematical foundations of multi-modal AI, this issue aims to enhance diagnostic precision, prognostic prediction, and personalized treatment planning. We welcome original research and reviews that push the boundaries of how automated systems interpret complex, multi-dimensional medical environments.
Dr. Sheng Lian
Dr. Zhiming Luo
Guest Editors
Manuscript Submission Information
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Keywords
- multi-modal learning
- medical image analysis
- mathematical modeling
- semantic enhancement
- representation learning
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