【摘要】：肺4D-CT圖像為放射治療提供了全面的圖像引導,它可以清楚地反映肺部靶區(qū)器官隨呼吸的運動規(guī)律,同時減少呼吸運動引起的偽影,為當今的肺癌治療提供了巨大的幫助。然而,肺4D-CT數(shù)據(jù)的采集時間長,劑量大,因此不能實現(xiàn)薄層厚的掃描,這導致采集到的肺4D-CT圖像層間分辨率顯著低于層內分辨率。因此想要觀察正常分辨率的肺4D-CT的Z軸圖像,必須要對的Z軸圖像按照一定比例進行插值。常用的插值方法有線性插值,三次樣條插值等,但是這些插值的方法都不能得到理想的重建結果。本文為了提高肺4D-CT圖像的多平面顯示的質量,研究了基于圖像超分辨率重建的方法,來重建高分辨率的肺4D-CT圖像。圖像超分辨率重建技術的基本思想是利用單幅或者多幅圖像的信息來提高圖像的顯示質量。常用的方法有基于頻域的方法和基于空域的方法�；陬l域的方法不易擴展,且不易添加約束。因此目前的研究主要集中在基于空域的超分辨率重建方法研究。本文針對肺4D-CT圖像特性,研究了兩種基于空間域處理的肺4D-CT圖像超分辨率重建:基于多相位圖像相似性和基于全局圖割的超分辨率重建方法。而且重建結果在視覺和量化方面,均優(yōu)于傳統(tǒng)的插值算法和POCS算法。本文的前兩章分別介紹了研究意義和相關技術現(xiàn)狀。在第三章和第四章分別詳細介紹了基于多相位相似性和基于全局圖割的超分辨率重建方法。其中第三章闡述了非局部均值濾波,基于多相位相似性的圖像塊搜素,以及全局約束重建。第四章闡述了全局圖的構造,能量函數(shù)構建及優(yōu)化求解。本文第五章對全文進行了總結和展望。
[Abstract]:Lung 4D-CT images provide a comprehensive image guide for radiotherapy, which can clearly reflect the movement of lung target organs with respiration, and reduce the artifacts caused by respiratory movements, which provides a great help for the treatment of lung cancer today. However, the collection time of lung 4D-CT data is long and the dose is large, so it is not possible to realize thin-layer thick scanning, which leads to the interlayer resolution of collected lung 4D-CT images being significantly lower than that of intralayer resolution. Therefore, in order to observe Z-axis images of lung 4D-CT with normal resolution, the Z-axis images must be interpolated in a certain proportion. The commonly used interpolation methods include linear interpolation, cubic spline interpolation and so on, but none of these interpolation methods can obtain ideal reconstruction results. In order to improve the quality of multiplanar display of lung 4D-CT images, a method based on super-resolution reconstruction is studied to reconstruct high-resolution lung 4D-CT images. The basic idea of image super-resolution reconstruction is to improve the display quality of images by using the information of single or multiple images. The commonly used methods are frequency-based and spatial-based methods. The method based on frequency domain is not easy to extend, and it is difficult to add constraints. Therefore, the present research focuses on spatial-based super-resolution reconstruction. According to the characteristics of lung 4D-CT images, two super-resolution reconstruction methods based on spatial domain processing for lung 4D-CT images are studied in this paper: one is based on the similarity of multi-phase images and the other is based on global image cutting. Moreover, the reconstruction results are superior to the traditional interpolation algorithm and POCS algorithm in vision and quantization. The first two chapters of this paper respectively introduce the significance of the research and the current situation of related technologies. In chapter 3 and chapter 4, the super-resolution reconstruction method based on multi-phase similarity and global graph cut is introduced in detail. In the third chapter, non-local mean filter, image block search based on multi-phase similarity, and global constrained reconstruction are discussed. In chapter 4, the construction of global graph, the construction of energy function and the optimization solution are discussed. The fifth chapter summarizes and prospects the full text.
【學位授予單位】：南方醫(yī)科大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R734.2;TP391.41

【參考文獻】

相關期刊論文 前7條

1 吳秀秀;肖珊;張煜;;基于配準的肺4D-CT圖像超分辨率重建[J];電子學報;2015年02期

2 王帥;;圖像插值算法綜述及分析[J];華章;2014年07期

3 蘇衡;周杰;張志浩;;超分辨率圖像重建方法綜述[J];自動化學報;2013年08期

4 張洪艷;沈煥鋒;張良培;李平湘;袁強強;;基于最大后驗估計的影像盲超分辨率重建方法[J];計算機應用;2011年05期

5 徐美芳;劉晶紅;;基于邊緣保持的航拍圖像凸集投影超分辨率重建算法[J];液晶與顯示;2010年06期

6 徐大宏;王潤生;;基于非局部正則化的圖像去噪[J];計算機應用研究;2009年12期

7 張書旭;周凌宏;陳光杰;林生趣;沈國輝;;4D-CT重建及其在肺癌放療中的應用研究進展[J];中國輻射衛(wèi)生;2008年03期

相關碩士學位論文 前1條

1 張銳娟;圖像配準理論及算法研究[D];西安電子科技大學;2009年

，

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