New Advances in Medical Image Processing

Dear Colleagues,

Medical image processing is a cornerstone of modern healthcare, profoundly influencing disease diagnosis, treatment planning, prognosis evaluation, and biomedical research. The rapid evolution of medical imaging technologies and the exponential growth of healthcare data present unprecedented opportunities for enhancing diagnostic precision and improving patient outcomes. From foundational tasks such as image reconstruction, quality enhancement, and multi-modal fusion to emerging challenges like cross-modal learning, personalized diagnostics, and interpretable AI systems, recent technological advances are continuously expanding the scope and depth of medical image applications. Meanwhile, the integration of deep learning, transformer-based architectures, and self-supervised paradigms is reshaping the landscape of medical image analysis, enabling more intelligent, automated, and clinically viable diagnostic tools.

This Special Issue focuses on cutting-edge developments in medical image processing, with a focus on innovative research in segmentation, classification, large-scale models, and related algorithmic approaches. We invite contributions that explore theoretical foundations and practical applications, addressing current limitations and proposing novel solutions in this rapidly evolving field.

Dr. Hui Ding
Guest Editor

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