Dynamically Adaptive Deformable Feature Fusion for Medical Imaging

This paper introduces dynamically adaptive deformable feature fusion techniques specifically designed for medical imaging applications. The method addresses the challenge of effectively combining multi-scale features in medical images while adapting to the spatial deformations inherent in biological structures.

Key Contributions

• Novel deformable feature fusion architecture
• Dynamic adaptation mechanisms for medical imaging
• Improved performance on various medical imaging tasks
• Robust handling of spatial deformations in biological structures

Applications

The proposed method has been successfully applied to various medical imaging tasks including:

• Hippocampal sclerosis measurement
• Arterial spin labeling asymmetry analysis
• General medical image analysis and segmentation

Impact

This work contributes to the advancement of computer vision techniques in medical imaging, providing more accurate and robust analysis tools for clinical applications.

Recommended citation: Jalali, A. et al. (2025). "Dynamically Adaptive Deformable Feature Fusion for Medical Imaging." Engineering Applications of Artificial Intelligence.
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