sMRI-based Diagnosis
收藏Figshare2026-02-19 更新2026-04-28 收录
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https://figshare.com/articles/dataset/_b_sMRI-based_Diagnosis_b_/31368412
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The model achieved an accuracy of 98.66%, outperforming existing fMRI- and EEG-based models. This highlights the potential of structural MRI in ADHD diagnosis, reducing dependence on more complex and resource-intensive imaging modalities. For ADHD segmentation, the Improved SwinUNet model was introduced, incorporating the CSIA module and ESDR module. The model achieved state-of-the-art segmentation performance with an IoU of 97.32% and a DSC of 97.50%.
创建时间：
2026-02-19
