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A subgroup-aware mixture-of-experts framework that couples group-level adaptation with patient-specific clinical guidance, enabling more reliable medical image analysis for individual patients is proposed.
Coronary Mask Guided Registration (CMGR) provides an effective approach for constructing continuous-time 4D cardiac CT datasets and can be used in system design simulations and in reconstruction algorithm development, thereby facilitating advances in cardiac CT imaging.
A Mixture of Multicenter Experts (MoME) framework to address AI bias in the medical domain without requiring data sharing across institutions is proposed and validated using a multimodal target volume delineation model for prostate cancer radiotherapy.
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