本文選題：口腔數(shù)字化 + 可視化�。� 參考：《浙江大學(xué)》2017年碩士論文

【摘要】：隨著三維掃描和錐體束CT等數(shù)據(jù)采集方式的普及,口腔領(lǐng)域的數(shù)字化得到了飛速發(fā)展�？谇活I(lǐng)域數(shù)據(jù)的可視化不僅僅局限于向醫(yī)生展示三維數(shù)據(jù),而且在通過三維處理和分析技術(shù)后,為醫(yī)生提供更為準(zhǔn)確的患者三維空間信息,從而輔助醫(yī)生進(jìn)行治療模擬、預(yù)測和評估。因此,口腔領(lǐng)域的數(shù)據(jù)可視化正逐漸成為可視化技術(shù)的研究熱點(diǎn)。本文介紹了三維處理和可視化若干技術(shù)在口腔數(shù)字化領(lǐng)域的相關(guān)應(yīng)用。在口腔三維模型處理方面,本文介紹了碰撞檢測、特征提取和分割、點(diǎn)云配準(zhǔn)等在口腔領(lǐng)域中的應(yīng)用。由于咬合干擾是口腔醫(yī)生非常關(guān)注的問題,本文介紹了基于Kd-Tree查找最近點(diǎn)對的碰撞檢測算法,并展示出患者上下牙頜模型之間的咬合接觸情況;在牙齒分割的領(lǐng)域,我們在前人基礎(chǔ)上提出了基于新的曲率特征提取和區(qū)域增長的自動牙齒分割算法,提高了牙齒分割的速度和精度;最后,我們將點(diǎn)云重建中基于近似一致點(diǎn)集的配準(zhǔn)方法應(yīng)用于口腔患者治療前后的匹配和比對,將患者治療前后的模型進(jìn)行配準(zhǔn)并計(jì)算偏差,幫助醫(yī)生評估治療的結(jié)果。在CBCT體數(shù)據(jù)的可視化方面,本文介紹了體數(shù)據(jù)和幾何數(shù)據(jù)的混合繪制方法,并將此應(yīng)用于口腔外科種植術(shù)中的種植釘定位和模擬放置領(lǐng)域。本方法可以向醫(yī)生更為直觀的展示種植體與患者牙槽骨的相對位置狀況,輔助醫(yī)生進(jìn)行種植體的放置。
[Abstract]:With the popularization of three-dimensional scanning and cone-beam CT, the digitalization of oral cavity has been developed rapidly. The visualization of oral data is not only limited to displaying 3D data to doctors, but also provides doctors with more accurate three-dimensional information of patients after 3D processing and analysis, which can help doctors to carry out treatment simulation. Prediction and evaluation Therefore, data visualization in the field of stomatology is becoming a hotspot in visualization technology. This paper introduces the application of three-dimensional processing and visualization technology in the field of oral cavity digitization. The applications of collision detection, feature extraction and segmentation, point cloud registration in the field of oral cavity are introduced in this paper. Because occlusal interference is a problem that dentists pay close attention to, this paper introduces a collision detection algorithm based on Kd-Tree to find the nearest point pair, and shows the occlusal contact between the upper and lower jaw models of patients, and in the field of tooth segmentation, On the basis of our predecessors, we propose an automatic tooth segmentation algorithm based on new curvature feature extraction and region growth, which improves the speed and accuracy of tooth segmentation. The registration method based on approximate consistent point set in point cloud reconstruction is applied to the matching and comparison of oral patients before and after treatment. The model of patients before and after treatment is registered and the deviation is calculated to help doctors evaluate the results of treatment. In the aspect of visualization of CBCT volume data, this paper introduces the hybrid rendering method of volume data and geometric data, and applies this method to the field of implant nail location and simulated placement in dental surgery. The method can show the relative position of implant and alveolar bone more intuitively to doctors and assist doctors in implant placement.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R78;TP391.41

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本文編號：1846376