NeuroBridge: Bridging Multi-Task MRI Knowledge for Neurodegenerative Disease Diagnosis
Summary
NeuroBridge is a clinically guided multi-task MRI framework for diagnosing Alzheimer's disease and mild cognitive impairment, achieving high accuracy and cross-cohort generalization.
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# NeuroBridge: Bridging Multi-Task MRI Knowledge for Neurodegenerative Disease Diagnosis Source: [https://arxiv.org/abs/2607.01401](https://arxiv.org/abs/2607.01401) [View PDF](https://arxiv.org/pdf/2607.01401) > Abstract:INTRODUCTION: Accurate MRI\-based identification of Alzheimer's disease \(AD\), mild cognitive impairment \(MCI\), and related dementias remains challenging because disease\-related structural changes are often subtle and heterogeneous\. We developed NeuroBridge, a clinically guided multi\-task MRI framework for neurodegenerative disease diagnosis\. METHODS: NeuroBridge integrates large\-scale self\-supervised MRI pretraining with hippocampal segmentation, hippocampal atrophy classification, and reconstruction objectives, followed by gated fusion fine\-tuning\. Performance was evaluated across ADNI and OASIS cohorts, including cross\-cohort transfer, probability\-based analysis, and opportunistic screening\. RESULTS: NeuroBridge achieved the highest performance across evaluated classification tasks, reaching 88\.17% accuracy for AD versus cognitively normal controls in ADNI and 82\.78% in OASIS\. The largest gains occurred in MCI\-related and mixed\-diagnosis settings\. The framework demonstrated strong cross\-cohort generalization, systematic associations between predicted\-class probability and accuracy, and the feasibility of probability\-based opportunistic screening\. DISCUSSION: Clinically guided multi\-task representation learning improves neurodegenerative MRI diagnosis beyond conventional single\-task approaches\. NeuroBridge provides a robust and scalable framework for dementia assessment and MRI\-based opportunistic screening\. ## Submission history From: Mengyu Li \[[view email](https://arxiv.org/show-email/647a5812/2607.01401)\] **\[v1\]**Wed, 1 Jul 2026 19:03:42 UTC \(7,645 KB\)
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