本文關鍵詞：三維醫(yī)學數(shù)據(jù)體繪制的傳輸函數(shù)設計方法研究　出處：《中國科學技術大學》2016年博士論文　論文類型：學位論文

  更多相關文章： 直接體繪制 醫(yī)學數(shù)據(jù)可視化 傳輸函數(shù) 邊界可視化 邊界提取 邊界檢測 遮擋

【摘要】：隨著現(xiàn)代醫(yī)學影像學和計算機技術的高速發(fā)展,三維醫(yī)學數(shù)據(jù)可視化在醫(yī)學影像的診斷與治療以及生物醫(yī)學研究中起到越來越關鍵的作用。其主要作用是幫助臨床醫(yī)生或研究人員直觀的看到并了解生物體內部的情況,尤其是他們感興趣的組織或結構的相互連接關系和幾何形狀大小。相比于傳統(tǒng)的二維切片顯示,三維醫(yī)學數(shù)據(jù)的可視化為用戶提供了更加逼真的顯示手段和定量的分析工具,便于用戶從多角度、多層次的觀察分析醫(yī)學影像,在輔助診斷、引導治療等方面都有著廣泛的應用。三維醫(yī)學數(shù)據(jù)可視化常用的一種方法是直接體繪制,傳輸函數(shù)是直接體繪制中最重要的步驟之一,它把三維醫(yī)學影像數(shù)據(jù)中每個體素的數(shù)值特征映射成為光學特征,如顏色和不透明度,實現(xiàn)具有真實感的三維圖像繪制。傳輸函數(shù)設計的好壞決定了可視化的質量的高低。本文的主旨在于研究高效的傳輸函數(shù)設計方法和體繪制交互方法,其目的都是避免復雜的交互式傳輸函數(shù)設計,提升醫(yī)學體繪制的效率。經典的基于邊界的傳輸函數(shù)設計,如f-|%絝|二維統(tǒng)計直方圖和LH二維統(tǒng)計直方圖,能夠快速的聚類和提取不同的邊界。然而,這兩種方法在噪聲干擾下,直方圖中邊界的聚類變得模糊,這導致邊界提取不完整和用戶交互復雜。由于各個角度體數(shù)據(jù)的投影不同,需要調節(jié)傳輸函數(shù)來使得感興趣的組織或結構得到突出顯示。然而,體繪制參數(shù)的調節(jié)對于沒有先驗知識的普通用戶來說,是一個反復嘗試而且耗時的過程。針對上述問題,本文從基于邊界的傳輸函數(shù)設計和體繪制參數(shù)的調節(jié)兩個方面,對上述算法進行改進,提升了邊界提取的可靠性和用戶交互的高效性。1、針對CT圖像,本文提出了一種基于動態(tài)的統(tǒng)計直方圖的傳輸函數(shù)設計方法。一方面,我們建立了一個通用的受噪聲干擾的邊界模型：另一方面,在此基礎之上,我們提出了一個新的基于邊界中值(M)、邊界高度(△h)和梯度(|%絝|)的多維傳輸函數(shù)設計方法。和傳統(tǒng)的統(tǒng)計直方圖呈現(xiàn)所有的邊界信息不同,我們提出的動態(tài)直方圖方法每次只顯示一種邊界。另外,還提出了一個簡單的邊界迭代提取策略：首先把所有邊界按照邊界高度由高到低排序,用戶控制△h的值由大到小直到有一個豎條出現(xiàn)在M-|%絝|直方圖中,邊界會被依次提取直到△h變?yōu)镺。得益于這個迭代提取策略,邊界間的誤分和受噪聲干擾得以降低；此外,由于區(qū)域消除和區(qū)域擴張的進一步運用,繪制質量得以提高。2、本文亦提出了一種所選即所得(what material you pick is what boundary you see)邊界體繪制傳輸函數(shù)設計方法。不同于傳統(tǒng)的直方圖的邊界傳輸函數(shù)設計方法是利用數(shù)學統(tǒng)計聚類實現(xiàn)的,我們首先提出了以用戶為中心的邊界提取的準則和基于這個準則改進的邊界模型,然后我們提出了一個所選即所得的邊界傳輸函數(shù)設計方法。一方面,用戶可以通過直接選擇感興趣的組織或結構來傳遞語義信息；另一方面,我們采用三維Canny邊緣檢測算子來確保邊界位置的可靠性。最后,我們建立了一個點到物體(point-to-material)的距離度量來確保邊界的準確性和完備性。整個基于邊界的傳輸函數(shù)設計方法都是直接在三維圖像上進行操作,設計過程具有很好地直觀性、實時性和精確度。3、直接體繪制把三維物體壓縮成二維圖像會造成深度信息的損失,這種損失主要表現(xiàn)為物體的遮擋。為了快速調節(jié)傳輸函數(shù)參數(shù)使得感興趣的組織或結構能在各個角度都能有清晰突出的顯示,本文首先提出可視比率(visibility ratio)和遮擋向量(occlusion vector)兩個定量描述遮擋的概念,這兩個概念都是直接來源于離散體繪制算法的推導。其次我們提出了一個交互式的線性反饋機制來調節(jié)傳輸函數(shù)的參數(shù)。整個反饋機制與經典的a顏色混合非常類似,用戶可以定量的了解遮擋和通過直覺調整參數(shù)。另外,傳輸函數(shù)參數(shù)調節(jié)不涉及到具體的傳輸函數(shù)設計方式,可以把傳輸函數(shù)參數(shù)調節(jié)方法集成到任意的以數(shù)據(jù)為中心的直接體繪制系統(tǒng)中作為一個重要的補充。經過大量的實驗證明,本文提出的傳輸函數(shù)設計和調節(jié)方法能較好的檢測和提取邊界,減少用戶的交互,提高醫(yī)學數(shù)據(jù)可視化的效率。
[Abstract]:With the rapid development of modern medical imaging and computer technology, 3D medical data visualization plays a more and more important role in medical imaging diagnosis and treatment as well as biomedical research. Its main role is to help clinicians or researchers intuitively see and understand the internal situation of organisms, especially the interconnections and geometry size of organizations or structures that they are interested in. Compared with the traditional 2D slice display, the visualization of 3D medical data display and analysis tools provides more realistic and quantitative for the user, is convenient for users to observe from the multi angle, multi-level analysis of medical images, are widely used in the diagnosis and treatment guide. A commonly used method of 3D visualization of medical data is direct volume rendering, the transfer function is one of the most important steps in direct volume rendering, the numerical characteristics of 3D medical image data and maps each voxel as optical characteristics, such as color and opacity, 3D image with photorealistic rendering. The quality of the visual quality is determined by the design of the transmission function. The purpose of this paper is to study efficient transmission function design method and volume rendering interaction method. The purpose is to avoid complex interactive transfer function design and improve the efficiency of medical volume rendering. The design of transfer function based on the classical boundary, such as f-|% Ku | two-dimensional statistical histogram and LH two-dimensional histogram, clustering and extraction can fast different boundary. However, under the noise interference, the clustering of the boundary in the histogram becomes blurred, which leads to the incomplete boundary extraction and the complexity of the user interaction. Because the projection of each angle body is different, it is necessary to adjust the transmission function to make the organization or structure of interest be highlighted. However, the adjustment of volume rendering parameters is a trial and time-consuming process for ordinary users without prior knowledge. To solve these problems, we improve the above algorithms from two aspects, which are boundary based transmission function design and parameter adjustment of volume rendering, which improves the reliability of boundary extraction and the efficiency of user interaction. 1. In view of the CT image, this paper presents a design method of the transmission function based on the dynamic statistical histogram. On the one hand, we establish a general model of the noise in the boundary. On the other hand, on this basis, we propose a new boundary based on median (M), boundary height (delta H) and gradient (|% Ku |) the multi-dimensional transfer function design method. And the traditional statistical histogram shows that all the boundary information is different. The dynamic histogram method proposed by us shows only one boundary each time. In addition, also proposed the strategy of extracting a simple iterative boundary: first of all according to the boundary boundary from low to high ranking, the user to control the delta H values from large to small until there is a bar in M-|% Ku | histogram, the boundary will be extracted in turn until the H is O. Thanks to the iterative extraction strategy, the erroneous points between boundaries and noise interference are reduced. Moreover, due to the further application of region elimination and region expansion, the rendering quality is improved. 2. This paper also presents a design method for the transfer function of the what material you pick is what boundary you see) boundary volume rendering. The boundary transfer function design method is different from the traditional histogram is the use of mathematical statistical clustering, we first propose a user centric boundary extraction criteria and improvement based on this criterion boundary model, then we propose a design method that is selected from the boundary of the transfer function. On the one hand, users can transmit semantic information directly by selecting organizations or structures of interest. On the other hand, we use three-dimensional Canny edge detection operators to ensure the reliability of boundary locations. Finally, we set up a distance measure of the point to object (point-to-material) to ensure the accuracy and completeness of the boundary. The transfer function design method based on boundary are operated directly on the three-dimensional image, the design process has very good direct view, real-time and accuracy. 3. The loss of depth information is caused by the compression of three-dimensional objects into two-dimensional images by direct volume rendering, which is mainly represented by the occlusion of the object. In order to quickly adjust the transfer function parameters to make the interests of the organization or structure can display clear and outstanding in all angles, this paper put forward visibility ratio (visibility ratio) and occlusion (occlusion vector) vector concept two quantitative description of occlusion, the two concepts are derived directly from the discrete rendering algorithm. Secondly, we propose an interactive linear feedback mechanism to adjust the parameters of the transmission function. The whole feedback mechanism is very similar to the classic a color mixing, and the user can quantify the occlusion and adjust the parameters by intuition. In addition, transfer function parameter adjustment does not relate to specific transmission function design. It can integrate transmission function parameter adjustment into any data centric direct volume rendering system as an important supplement. After a lot of experiments, it is proved that the transmission function design and adjustment method proposed in this paper can better detect and extract boundaries, reduce user interaction and improve the visualization efficiency of medical data.
【學位授予單位】：中國科學技術大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：TP391.41;R318

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