Stomatology ›› 2025, Vol. 45 ›› Issue (6): 445-452.doi: 10.13591/j.cnki.kqyx.2025.06.009
• Basic and Clinical Research • Previous Articles Next Articles
LIU Fei1,2,3, ZHANG Jiulou4(), JIN Ruofan1,2,3, ZHANG Nan1,2,3, ZHOU Weina1,2,3(
)
Received:
2024-12-29
Online:
2025-06-28
Published:
2025-07-08
CLC Number:
LIU Fei, ZHANG Jiulou, JIN Ruofan, ZHANG Nan, ZHOU Weina. The automatic segmentation of the temporomandibular joint based on MRI using deep learning method[J]. Stomatology, 2025, 45(6): 445-452.
Tab.3
The Dice, Recall, Precision and F1 score of 2D/3D model in the close or open mouth images"
模型 | 图像类别 | 关节组织 | Dice | 召回率 | 精确率 | F1分数 |
---|---|---|---|---|---|---|
2D模型 | 闭口位 | 关节盘 | 0.775 911 | 0.761 949 | 0.802 372 | 0.781 638 |
髁突 | 0.861 552 | 0.858 067 | 0.880 847 | 0.869 308 | ||
关节窝 | 0.661 321 | 0.613 758 | 0.717 471 | 0.661 574 | ||
开口位 | 关节盘 | 0.790 665 | 0.788 616 | 0.807 662 | 0.798 026 | |
髁突 | 0.899 456 | 0.901 339 | 0.908 778 | 0.905 043 | ||
关节窝 | 0.662 487 | 0.624 911 | 0.711 179 | 0.665 260 | ||
3D模型 | 闭口位 | 关节盘 | 0.778 488 | 0.748 471 | 0.821 614 | 0.783 339 |
髁突 | 0.869 087 | 0.871 318 | 0.882 744 | 0.876 994 | ||
关节窝 | 0.680 833 | 0.643 324 | 0.722 766 | 0.680 735 | ||
开口位 | 关节盘 | 0.796 855 | 0.781 431 | 0.827 924 | 0.804 006 | |
髁突 | 0.902 941 | 0.906 160 | 0.912 518 | 0.909 328 | ||
关节窝 | 0.680 003 | 0.650 240 | 0.716 696 | 0.681 853 |
Tab.4
Results of One-way ANOVA test:there was no significant difference in the segmentation ability of the four models(2D/3D models in the open and closed images)"
关节组织 | 平方和 | 自由度 | 均方 | F | P | |
---|---|---|---|---|---|---|
关节盘 | 组间 | 0.006 | 3 | 0.002 | 0.350 | 0.789 |
组内 | 0.429 | 76 | 0.006 | |||
总计 | 0.435 | 79 | ||||
髁突 | 组间 | 0.026 | 3 | 0.009 | 1.998 | 0.121 |
组内 | 0.335 | 76 | 0.004 | |||
总计 | 0.362 | 79 | ||||
关节窝 | 组间 | 0.007 | 3 | 0.002 | 0.376 | 0.771 |
组内 | 0.263 | 57 | 0.005 | |||
总计 | 0.471 | 79 |
Tab.5
Results of One-way ANOVA test:there were statistical differences in the segmentation effect of the three joint tissues(articular disc,condyle,and glenoid fossa)"
模型 | 平方和 | 自由度 | 均方 | F | P | |
---|---|---|---|---|---|---|
2D/闭口位 | 组间 | 0.404 | 2 | 0.202 | 34.933 | <0.001 |
组内 | 0.329 | 57 | 0.006 | |||
总计 | 0.733 | 59 | ||||
3D/闭口位 | 组间 | 0.355 | 2 | 0.177 | 30.568 | <0.001 |
组内 | 0.331 | 57 | 0.006 | |||
总计 | 0.685 | 59 | ||||
2D/开口位 | 组间 | 0.563 | 2 | 0.281 | 52.560 | <0.001 |
组内 | 0.305 | 57 | 0.005 | |||
总计 | 0.868 | 59 | ||||
3D/开口位 | 组间 | 0.497 | 2 | 0.249 | 53.872 | <0.001 |
组内 | 0.263 | 57 | 0.005 | |||
总计 | 0.761 | 59 |
Tab.6
The diagnostic accuracy of ADD by young doctors based on the original MRI image and the segmentation results of 2D and 3D models(with the senior doctor’s diagnosis for the correct diagnosis) %"
诊断依据 | 正常 | ADDwR | ADDwoR | 总计 |
---|---|---|---|---|
原图 | 66.7 | 83.3 | 88.9 | 82.5 |
2D网络分割图 | 88.9 | 100 | 100 | 97.5 |
2D网络分割图 | 88.9 | 100 | 100 | 97.5 |
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