【摘要】：錯頜畸形指牙齒排列不整齊、上下牙齒咬合不正確等現(xiàn)象,其不僅影響頜面外觀而且影響頜面健康,給患者帶來身心傷害。錯頜畸形主要通過臨床口腔正畸治療進(jìn)行矯治�；诨颊呖谇籆T圖像,可重構(gòu)出牙齒三維數(shù)字模型,為正畸醫(yī)生制定矯治方案和實(shí)施正畸治療提供重要信息。而口腔CT圖像中各個獨(dú)立牙齒輪廓的分割是重構(gòu)牙齒三維模型的關(guān)鍵環(huán)節(jié)。由于相鄰牙齒通常粘連一起、牙根鑲嵌在牙槽骨中、牙冠牙根拓?fù)浣Y(jié)構(gòu)不一致等問題,口腔CT圖像中獨(dú)立牙齒輪廓分割一直是計(jì)算機(jī)輔助口腔正畸領(lǐng)域中的一個技術(shù)難點(diǎn),本文擬對該問題展開研究。首先在口腔CT圖像中進(jìn)行獨(dú)立牙齒區(qū)域分離。將各層口腔CT圖像沿牙弓曲線展開,投影合成全景圖。檢測全景圖中上下頜之間、相鄰牙齒之間灰度較低的像素形成牙齒上下頜分離線及相鄰牙齒分離線。再根據(jù)相鄰牙齒分離線確定三維空間中相鄰牙齒間的分離曲面,實(shí)現(xiàn)獨(dú)立牙齒區(qū)域的分離。將獨(dú)立牙齒區(qū)域在兩個相互垂直投影面上投影,通過提取投影圖像中的牙齒輪廓得到二維軸線,再把兩根二維軸線合成的三維軸線作為獨(dú)立牙齒的長軸方向。然后根據(jù)長軸方向旋轉(zhuǎn)獨(dú)立牙齒區(qū)域并進(jìn)行圖像轉(zhuǎn)換,使轉(zhuǎn)換后的獨(dú)立牙齒區(qū)域相鄰圖像間的牙齒輪廓具有相似性。采用混合水平集算法分割旋轉(zhuǎn)后的獨(dú)立牙齒區(qū)域中的牙齒輪廓。先從獨(dú)立牙齒區(qū)域的牙頸部位選擇一張切片并手工分割該切片上的牙齒輪廓,其結(jié)果作為初始牙齒輪廓。然后從初始切片開始分別沿兩個相反的方向進(jìn)行牙齒輪廓自動傳播。輪廓傳播時以上一張切片的輪廓作為先驗(yàn),通過構(gòu)建的混合水平集能量函數(shù)對牙齒輪廓的傳播進(jìn)行控制。使用5個患者的口腔CT圖像對提出的分割算法進(jìn)行了測試,測試結(jié)果表明,本文提出的獨(dú)立牙齒輪廓分割算法可以得到良好的分割結(jié)果。
[Abstract]:Malocclusion refers to the irregular arrangement of teeth and incorrect occlusion of upper and lower teeth, which not only affects the appearance of maxillofacial, but also affects the health of maxillofacial, and brings physical and mental injury to patients. Malocclusion is mainly treated by orthodontic treatment. Based on the CT images of patients with oral cavity, the three-dimensional digital model of teeth can be reconstructed, which can provide important information for orthodontists to formulate orthodontic treatment plans and implement orthodontic treatment. The segmentation of individual tooth contours in oral CT images is the key to reconstruct the 3D model of teeth. Due to the conglutination of adjacent teeth, the root embedded in the alveolar bone and the inconsistent topologic structure of the crown and root, the contour segmentation of the independent teeth in CT images has always been a technical difficulty in the field of computer-aided orthodontics. This paper intends to study this problem. At first, CT images were used to separate the region of individual teeth. The CT images of each layer of oral cavity were expanded along the curve of dental arch, and the panoramic images were projected and synthesized. The pixels in panoramic images with lower grayscale between upper and lower mandibles and between adjacent teeth form the line of separation between upper and lower teeth and adjacent lines of teeth. Then according to the separation line of adjacent teeth, the separation surface between adjacent teeth in three dimensional space is determined to realize the separation of independent tooth regions. The independent tooth region is projected on two vertical projection planes of each other. By extracting the tooth contour from the projection image, the 2D axis is obtained, and the three-dimensional axis composed of the two 2D axes is taken as the long axis direction of the independent tooth. Then the independent tooth region is rotated according to the long axis and the image conversion is carried out to make the tooth contour of adjacent images of the transformed independent tooth region similar. A hybrid level set algorithm is used to segment the tooth contour in the rotating independent tooth region. First, a slice is selected from the neck of the independent tooth region and the tooth contour on the slice is manually segmented, and the result is taken as the initial tooth contour. Then the tooth contour propagates automatically in two opposite directions from the initial section. The profile of the section above is used as a priori to control the propagation of the tooth contour by constructing a mixed level set energy function. The proposed segmentation algorithm is tested using oral CT images of five patients. The test results show that the proposed algorithm can achieve good segmentation results.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R783.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 楊耀;陳健美;魯海英;;基于標(biāo)記提取的GrowCut自動分割算法[J];信息技術(shù);2015年05期

2 曹巍;;基于形態(tài)學(xué)的三維牙齒模型分割算法[J];現(xiàn)代計(jì)算機(jī)(專業(yè)版);2015年06期

3 沈?yàn)?程小青;曾丹;;基于邊緣特征學(xué)習(xí)的自然圖像對稱軸檢測[J];上海大學(xué)學(xué)報(自然科學(xué)版);2014年06期

4 劉梟雄;石峰;張繼武;;基于三角網(wǎng)格演化的CBCT牙齒圖像分割方法[J];中國醫(yī)療器械雜志;2011年06期

5 馬亞奇;李忠科;王先澤;;基于測地路徑的牙齒模型交互分割算法研究[J];中國圖象圖形學(xué)報;2011年04期

6 楊玲;王中科;王云鵬;;牙縫約束下模糊連接法對單顆牙齒的分割[J];計(jì)算機(jī)工程與設(shè)計(jì);2009年21期

7 李文玉;王鈺;王靖;;對在CT中不可見相鄰齒廓線自動重構(gòu)的研究[J];計(jì)算機(jī)仿真;2009年05期

8 郝國棟;程筱勝;戴寧;俞青;;基于形態(tài)學(xué)的牙齒模型交互分割[J];中國制造業(yè)信息化;2008年01期

9 張飛;樊瑜波;蒲放;劉展;;牙頜CT圖像序列中牙的半自動分割方法[J];生物醫(yī)學(xué)工程學(xué)雜志;2007年01期

10 高斌;宋小文;胡樹根;俞小莉;;基于流形的封閉曲線光順優(yōu)化插值方法[J];農(nóng)業(yè)機(jī)械學(xué)報;2006年10期

相關(guān)博士學(xué)位論文 前3條

1 龍建武;圖像閾值分割關(guān)鍵技術(shù)研究[D];吉林大學(xué);2014年

2 陽樹洪;灰度圖像閾值分割的自適應(yīng)和快速算法研究[D];重慶大學(xué);2014年

3 李佐勇;基于統(tǒng)計(jì)和譜圖的圖像閾值分割方法研究[D];南京理工大學(xué);2010年

相關(guān)碩士學(xué)位論文 前1條

1 劉艷霞;封閉圖形對稱軸的研究與應(yīng)用[D];吉林大學(xué);2015年

，

本文編號：2282822