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Radiology：AI在膝关节MR上的价值

2018-04-25 shaosai MedSci原创

磁共振膝关节软骨
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本研究旨在分析与手动分割相比，自动分割的准确性和精确性以及使用定量磁共振（MR）来研究膝关节退行性变如骨性关节炎（OA）的效率和准确性，并将结果发表在Radiology上。

本研究旨在分析与手动分割相比，自动分割的准确性和精确性以及使用定量磁共振（MR）来研究膝关节退行性变如骨性关节炎（OA）的效率和准确性，并将结果发表在Radiology上。

本研究共对638例磁共振数据进行分析，其中包括T1 ρ和3D DESS图像。在U网卷积网络结构的基础上建立深度学习模型来进行自动分割。以有经验的放射科医生手动分割结果为对照。利用Dice系数评价自动分割的表现。

结果为，该模型产生较强的Dice系数，尤其是对于3D-DESS图像，软骨、外侧半月板和内侧半月板系数范围分别在0.770-0.878、0.809-0.753。该模型平均5秒左右完成分割。T1ρ 和T2在手动和自动分割间平均相关性为0.8233、0.8603，体积和厚度分别为0.9349、0.9384。自动分割方法的纵向精确性与手动分割大约一致。

本研究表明，U网在快速准确分割方面具有较高效率和准确性，可通过提取弛豫时间和形态学特征来监管和诊断OA。

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    2018-04-28 xiaotao112411

    学习学习学习

    0

  5. 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createdAvatar=https://cdnapi.center.medsci.cn/medsci/head/2017/11/05/dc628308c49d4aa82335673176ebb6d3.jpg, createdBy=153c1955083, createdName=xiaotao112411, createdTime=Thu Apr 26 08:14:47 CST 2018, time=2018-04-26, status=1, ipAttribution=)]
    2018-04-28 xiaotao112411

    学习学习学习

    0

  6. 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createdAvatar=https://cdnapi.center.medsci.cn/medsci/head/2017/11/05/dc628308c49d4aa82335673176ebb6d3.jpg, createdBy=153c1955083, createdName=xiaotao112411, createdTime=Thu Apr 26 08:14:47 CST 2018, time=2018-04-26, status=1, ipAttribution=)]
    2018-04-28 xiaotao112411

    学习学习学习

    0

  7. 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createdAvatar=https://cdnapi.center.medsci.cn/medsci/head/2017/11/05/dc628308c49d4aa82335673176ebb6d3.jpg, createdBy=153c1955083, createdName=xiaotao112411, createdTime=Thu Apr 26 08:14:47 CST 2018, time=2018-04-26, status=1, ipAttribution=)]
    2018-04-28 xiaotao112411

    学习学习学习

    0

  8. 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createdAvatar=https://cdnapi.center.medsci.cn/medsci/head/2017/11/05/dc628308c49d4aa82335673176ebb6d3.jpg, createdBy=153c1955083, createdName=xiaotao112411, createdTime=Thu Apr 26 08:14:47 CST 2018, time=2018-04-26, status=1, ipAttribution=)]
    2018-04-28 131****1460

    学习了受益匪浅

    0

  9. 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    2018-04-26 xiaotao112411

    学习学习学习

    0

  10. 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    2018-04-26 xiaotao112411

    学习学习学习

    0

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