The proposed neural architecture search method effectively detects bone metastasis in bone scintigrams and outperforms existing state-of-the-art approaches, demonstrating that incorporating manual network design experience into the architecture search process can significantly improve model performance.
An improved YOLO11-based detection model incorporating a Mamba-inspired architecture and a Dynamic Upsampling module is adopted in the neck network to improve multi-scale feature fusion and enhance the localization capability for lesion areas.
This review provides a comprehensive overview of MMIF from theoretical and technical perspectives and presents current challenges and future development trends of MMIF, including robustness, clinical translation, and emerging multimodal learning paradigms.
Pengquan Han, Cui-Yin Liu, Cuiwei Wang· Italian National Conference...· 0 citations
Pelvic MRI fistulogram offers better contrast in soft-tissue and multi-planar image viewing, which are very important for accurate diagnosis and efficient treatment planning, and has become the ultimate choice for the evaluation of RVF.
Faikah Awang, Muhammad Khalis, Abdul Karim et al.· Current medical imaging· 25 citations
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