【摘要】：超聲成像技術(shù)具有無損、實(shí)時成像、價格低廉和使用便捷等優(yōu)點(diǎn),是產(chǎn)前診斷中最常用的檢查手段。在常規(guī)的產(chǎn)前超聲檢查中,胎兒的小腦是必要的檢查部位。小腦的橫徑和體積是醫(yī)生評估胎兒發(fā)育狀況和健康程度的重要指標(biāo),而小腦的形態(tài)和完整性是診斷先天性畸形的參考標(biāo)準(zhǔn)。然而,超聲圖像的低信噪比特性給定量分析和診斷帶來了不利影響。臨床應(yīng)用中,超聲診斷往往存在準(zhǔn)確性因醫(yī)生經(jīng)驗(yàn)而異、三維特征分析耗時等缺陷。因此,在超聲圖像分析中引入自動特征提取和特征分析方法具有重要的意義。本論文的研究目標(biāo)是開發(fā)一種創(chuàng)新的、高效的計算機(jī)輔助診斷方法,在無需人工干預(yù)的前提下,實(shí)現(xiàn)胎兒小腦三維超聲容積的全自動分割和特征分析�；诖四康�,本論文對超聲圖像的顯著特征提取、目標(biāo)結(jié)構(gòu)定位、相位對稱性提取及分割等方法進(jìn)行了研究,工作內(nèi)容包括以下四方面：1)實(shí)現(xiàn)圖像顯著特征的提取。在三維超聲容積的中心切面上,胎兒的腦中線是最顯著的特征,因?yàn)槟X中線的灰度值較高、呈直線形狀；其次是胎兒的頭顱,面積較大、呈橢圓形�；谶@些特征,本論文提出應(yīng)用加權(quán)霍夫變換算法檢測胎兒的腦中線,通過高斯函數(shù)改變圖像的灰度分布,提高直線檢測的準(zhǔn)確性。此外,應(yīng)用約束型隨機(jī)霍夫變換算法提取胎兒的頭顱，而通過約束點(diǎn)輔助橢圓擬合,提高算法的收斂速度。2)針對胎兒小腦面積較小、形狀不規(guī)則以及邊緣特征不明顯等特征,提出了一種結(jié)合顯著特征提取和遍歷式搜索的間接定位方法。該定位方法將圖像的顯著特征和小腦的先驗(yàn)知識嵌入一種樹形結(jié)構(gòu)的概率型分類器,將小腦可能出現(xiàn)的位置約束在較小的范圍內(nèi)。然后,利用圓形濾波器進(jìn)行遍歷式搜索,對胎兒小腦進(jìn)行精確定位。3)針對三維活動表面模型分割算法對初始模型敏感的缺點(diǎn),將小腦的定位結(jié)果擴(kuò)展至三維空間,作為分割的初始模型；針對該分割算法的弱邊緣泄露問題,提出利用方向性相位對稱性構(gòu)造能量函數(shù)。方向性相位對稱性將小腦的感興趣區(qū)域分裂成若干個子區(qū)域,對各個子區(qū)域自適應(yīng)地選擇最匹配的濾波器角度,從而增強(qiáng)小腦邊緣的清晰度和連續(xù)性、抑制圖像的噪聲,提高分割的準(zhǔn)確性。4)基于分割的胎兒小腦三維模型進(jìn)行特征分析,考察小腦左右半球的對稱性以及小腦體積、橫徑和質(zhì)心距與胎齡的相關(guān)性,并分別計算出相應(yīng)的回歸方程。
[Abstract]:Ultrasonic imaging technology has the advantages of lossless, real-time imaging, low cost and convenient use. It is the most commonly used means of prenatal diagnosis. In routine prenatal ultrasound examination, fetal cerebellum is a necessary part of examination. The transverse diameter and volume of the cerebellum are important indexes for doctors to evaluate the fetal development and health, and the shape and integrity of the cerebellum are the reference criteria for the diagnosis of congenital malformations. However, the low signal-to-noise ratio (SNR) characteristics of ultrasonic images have a negative impact on quantitative analysis and diagnosis. In clinical application, the accuracy of ultrasonic diagnosis varies with the doctor's experience, and the analysis of three-dimensional features is time-consuming and so on. Therefore, it is of great significance to introduce automatic feature extraction and feature analysis methods into ultrasonic image analysis. The aim of this paper is to develop an innovative and efficient computer-aided diagnosis method, which can realize automatic segmentation and feature analysis of three-dimensional ultrasound volume of fetal cerebellum without manual intervention. For this purpose, the methods of ultrasonic image salient feature extraction, target structure localization, phase symmetry extraction and segmentation are studied in this paper. The main contents are as follows: 1) realizing the extraction of image salient features. On the center section of three-dimensional ultrasound volume, the midline of the fetal brain is the most obvious feature, because the gray value of the midline of the brain is high, and the shape of the line is straight, and the next is the fetal head, with a larger area and an oval shape. Based on these features, this paper proposes to use weighted Hough transform algorithm to detect the midline of fetal brain, and to improve the accuracy of line detection by changing the gray distribution of the image through Gao Si function. In addition, the constrained random Hough transform algorithm is used to extract the fetal head, while the constraint point-assisted ellipse fitting is used to improve the convergence rate of the algorithm. 2) the fetal cerebellar area is smaller. Because the shape is irregular and the edge features are not obvious, an indirect localization method is proposed, which combines significant feature extraction and ergodic search. In this method, the salient features of the image and the prior knowledge of the cerebellum are embedded into a tree-structured probabilistic classifier, and the possible location of the cerebellum is limited to a smaller range. Then, the circular filter is used for ergodic search to accurately locate the fetal cerebellum. 3) aiming at the disadvantage that the 3D active surface model segmentation algorithm is sensitive to the initial model, the cerebellar localization results are extended to three-dimensional space. As the initial model of segmentation; In order to solve the weak edge leakage problem of the segmentation algorithm, an energy function is constructed by using directional phase symmetry. The directional phase symmetry divides the region of interest of the cerebellum into several sub-regions, and adaptively selects the best matching filter angle for each sub-region, thereby enhancing the clarity and continuity of the cerebellar edge and suppressing the noise of the image. 4) based on the segmented three-dimensional model of fetal cerebellum, the symmetry of the left and right hemispheres of cerebellum and the correlation of cerebellar volume, transverse diameter and centroid distance with gestational age were investigated. The corresponding regression equations are calculated respectively.
【學(xué)位授予單位】：復(fù)旦大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：R714.5;TP391.41

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本文編號：2445157