中国医疗器械杂志
中國醫療器械雜誌
중국의료기계잡지
CHINESE JOURNAL OF MEDICAL INSTRUMENTATION
2013年
4期
258-263
,共6页
郑彩仙%许修%王成%叶秀霞
鄭綵仙%許脩%王成%葉秀霞
정채선%허수%왕성%협수하
牙齿MRI-UTE图像%分割流程%分层约束%水平集
牙齒MRI-UTE圖像%分割流程%分層約束%水平集
아치MRI-UTE도상%분할류정%분층약속%수평집
Teeth MRI-UTE image%segmentation process%layer-dependent multi-constrained%level set
目的对MRI-UTE序列图像中的牙齿进行有效的分割。方法建立分层约束的二次分割算法流程。首先用水平集方法从用户在参考层中选定的区域内分割出牙齿边界;然后将已分割区域的信息作为下一层分割的约束,用水平集方法将边界向牙冠和牙根两个方向逐层演化;最后将相邻两层的分割结果作为约束,以重叠指数作为演化方程中的参数逐层进行二次分割以矫正结果。结果首次分割平均准确率为86.98%,二次分割后的准确率显著提高至88.35%,与其他两种方法相比改善效果具有统计学意义(P<0.05)。结论上述算法流程能有效应用于牙齿MRI-UTE序列图像的分割,在准确性上有了较大的改进。
目的對MRI-UTE序列圖像中的牙齒進行有效的分割。方法建立分層約束的二次分割算法流程。首先用水平集方法從用戶在參攷層中選定的區域內分割齣牙齒邊界;然後將已分割區域的信息作為下一層分割的約束,用水平集方法將邊界嚮牙冠和牙根兩箇方嚮逐層縯化;最後將相鄰兩層的分割結果作為約束,以重疊指數作為縯化方程中的參數逐層進行二次分割以矯正結果。結果首次分割平均準確率為86.98%,二次分割後的準確率顯著提高至88.35%,與其他兩種方法相比改善效果具有統計學意義(P<0.05)。結論上述算法流程能有效應用于牙齒MRI-UTE序列圖像的分割,在準確性上有瞭較大的改進。
목적대MRI-UTE서렬도상중적아치진행유효적분할。방법건립분층약속적이차분할산법류정。수선용수평집방법종용호재삼고층중선정적구역내분할출아치변계;연후장이분할구역적신식작위하일층분할적약속,용수평집방법장변계향아관화아근량개방향축층연화;최후장상린량층적분할결과작위약속,이중첩지수작위연화방정중적삼수축층진행이차분할이교정결과。결과수차분할평균준학솔위86.98%,이차분할후적준학솔현저제고지88.35%,여기타량충방법상비개선효과구유통계학의의(P<0.05)。결론상술산법류정능유효응용우아치MRI-UTE서렬도상적분할,재준학성상유료교대적개진。
Objective To introduce algorithms for effective segmentation of teeth MRI-UTE image. Methods To contruct second-segmentation algorithm process based on layer-dependent multi-constrained method. Firstly, a level set method was used to segment the initial boundary from the region determined by user in the reference slice. Secondly, both crown and root of the tooth were segmented by the improved level set method which took the information of the former layer's result as constraint conditions. Final y, the improved level set based on the information of the former and later layer’s results was executed for the second time to improve the accuracy of segmentation, in which, the parameter of the overlapping ratio was considered. Results The accuracy was 86.98% for the first-segmentation and was increased to 88.35% for the second-segmentation. Compared to the two other methods, the accuracy of the algorithms provided was improved significantly (P<0.05). Conclusions The proposed algorithms can effectively achieve the segmentation of teeth MRI-UTE image and has a great improvement on accuracy.