光学相干层析视网膜体数据的3维分割

提出一种光学相干层析(OCT)视网膜体数据3维分割的新方法.综合利用视网膜边界方向、图像强度峰值及分而治之的策略,可分割出多层重要边界面.具体过程是:在OCT体数据中,从上到下查找A-scan的第1个峰值确定内界膜(ILM)的初始位置,再通过表面光滑性约束去除异常点进行优化；利用类似的方法从下到上查找A-scan的第1个峰值定位视网膜色素上皮层(RPE)；然后,对由ILM和RPE之间的数据构成的子体,确定每条A-scan的亮度最大值分割出内外节层(IS/OS)上边界表面；最后,对由ILM和IS/OS之间的数据构成的子体,从下到上寻找A-scan的第1个峰值定位内核层和外网织层(INL/OPL)之间的边界表面.实验结果表明,本文方法在普通台式计算机上能够正确地分割出上述4个边界面,且每个边界面的分割可在几秒内完成.  

光学相干层析术在医学中的应用

光学相干层析术是从强散射介质中获取图像最有前途的一种新技术，介绍了其组成和工作原理以及在眼科、心血管系统、消化系统等医学领域的成功应用。  

基于HOG的眼前房角OCT图像分类

眼前房角开合程度的准确评价对于原发性闭角型与开角型青光眼的排查与治疗至关重要。为了从眼前房角OCT图像中,准确的评估各房角开放程度,采用了梯度方向直方图(HOG)图像特征描述眼前房角特征,利用图像中高维的视觉特征取代医学解剖特征,结合模式识别中较优的支持向量机分类方法,实现了眼前房角不同开放程度的评估。实验结果表明:HOG特征结合多分类支持向量机方法的应用能较优的实现不同成像质量下的房角开放程度的准确分类。  

基于ARM-Linux的嵌入式光学相干层析成像系统的研究

分析了相位对照光学相干层析成像的基本原理,并基于ARM9架构的嵌入式微处理器S3C2440和当前主流嵌入式的Linux多用户操作系统,提出了一套用于无损检测高分子聚合物有机复合材料的相位对照光学相干层析成像系统的设计方案。详细介绍了系统的原理及搭建过程,使用相位对照理论分析方法和表面变形测量方法并通过实验获得高分子聚合物有机复合材料内部结构的分布图。实验结果表明该嵌入式光学相干层成像系统是可行的。  

眼前节组织OCT图像边缘检测及特征角点提取

提出了一种适用于眼前节组织OCT图像的边缘检测算法。该算法在单尺度下用多个结构元素进行边缘检测,根据边缘图像灰阶值的差异性,采用动态自适应权重进行像素点融合;再利用连通域的方法抹去面积小的干扰区域,最终得到多结构元素单尺度边缘检测图像,并在其上通过象限区间有效地提取出了角膜特征角点。仿真结果表明边缘特征明显,较以往边缘检测算法有效避免了OCT图像边缘结果的突变像素点的出现,抹去了干扰区域。因此,提出的特征角点具有较高的准确性。  

基于稀疏表示的频域OCT图像降噪技术研究

在压缩感知理论的基础上提出了一种非规则采样层析数据的重建方法, 主要研究了频域光学相关层析(SDOCT)数据的降噪问题。采用传统的B-scans扫描模式得到一系列具有高SNR的图像, 对每一幅高SNR图像训练得到一个稀疏表示字典, 然后由所得到的稀疏表示字典对低SNR的B-scans图像进行降噪, 称这种方法为多层稀疏层析降噪算法(MSBTD)。其基本原理是在通常的SDOCT数据中, 相邻的B-scans数据具有相同的结构和噪声类型。其优点在于其不需要在大多数方位向获取超过一个B-scans数据, 因此会明显降低扫描时间。尽管稀疏表示方法在图像处理领域得到了广泛的应用, 但是MSBTD算法的最大创新点在于其结合了一种常用的扫描算法, 使其适用于医学上的SDOCT处理。仿真表明MSBTD算法能够取得优于传统降噪方法的结果。  

Automated segmentation of macular layers in OCT images and quantitative evaluation of performances

Optical coherence tomography (OCT) allows high-resolution and noninvasive imaging of the structure of the retina in humans. This technique revolutionized the diagnosis of retinal diseases in routine clinical practice. Nevertheless, quantitative analysis of OCT scans is yet limited to retinal thickness measurements. We propose a novel automated method for the segmentation of eight retinal layers in these images. Our approach is based on global segmentation algorithms, such as active contours and Markov random fields. Moreover, a Kalman filter is designed in order to model the approximate parallelism between the photoreceptor segments and detect them. The performance of the algorithm was tested on a set of retinal images acquired in-vivo from healthy subjects. Results have been compared with manual segmentations performed by five different experts, and intra and inter-physician variability has been evaluated as well. These comparisons have been carried out directly via the computation of the root mean squared error between the segmented interfaces, region-oriented analysis, and retrospectively on the thickness measures derived from the segmentations. This study was performed on a large database including more than seven hundred images acquired from more than one hundred healthy subjects.  

Minimising retinal vessel artefacts in optical coherence tomography images

Optical coherence tomography (OCT) is commonly used to investigate the layers of the retina including retinal nerve fiber layer (RNFL) and retinal pigment epithelium (RPE). OCT images are altered by vessels on the retinal surface producing artefacts. We propose a new approach to compensate for these artefacts and enhance quality of OCT images. A total of 28 (20 normal and 8 glaucoma subjects) OCT images were obtained using Spectralis (Heidelberg, Germany). Shadows were detected along the image and compensated by the A-Scan intensity difference from surrounding non-affected areas. Images were then segmented and the area and thickness of RNFL and RPE were measured and compared. 10 subjects were tested twice to determine the effect of this on reproducibility of measurements. Shadow-suppressed images reflected the profile of the retinal layers more closely when assessed qualitatively, minimising distortion. The segmentation of RNFL and RPE thickness demonstrated a mean change of 2.4% ± 1 and 6% ± 1 from the original images. Much larger changes were observed in areas with vessels. Reproducibility of RNFL thickness was improved, specifically in the higher density vessel location, i.e. inferior and superior. Therefore, OCT images can be enhanced by an image processing procedure. Vessel artefacts may cause errors in assessment of RNFL thickness and are a source of variability, which has clinical implications for diseases such as glaucoma where subtle changes in RNFL need to be monitored accurately over time.  

Dynamic variation of hemodynamic shear stress on the walls of developing chick hearts: computational models of the heart outflow tract

Heart morphogenesis and growth are influenced by hemodynamic forces (wall shear stress and blood pressure) acting on the walls of the heart. Mechanisms by which hemodynamic forces affect heart development are not well understood, in part because of difficulties involved in measuring these forces in vivo. In this paper, we show how wall shear stress in the heart outflow tract (OFT) of chick embryos at an early developmental stage (HH18) are affected by changes in the geometry and motion of the OFT wall. In particular, we were interested in the effects of cardiac cushions, which are protrusions of the OFT wall toward the lumen and that are located where valves will later form. We developed idealized finite element models (FEM) of the chick OFT with and without cardiac cushions. Geometrical parameters used in these models were estimated from in vivo images obtained using optical coherence tomography (OCT) techniques. The FEMs showed significant reverse blood flow (backflow) in the OFT, consistent with experimental observations in the chick heart at HH18, and revealed that cardiac cushions decrease backflow. In addition, our FEMs showed that the spatial distribution of wall shear stress is affected by cardiac cushions, with larger absolute peak values observed at the cushions. Differences in mechanical stimuli (wall shear stress) that the cells in the cardiac cushions and elsewhere are subjected to may affect valve formation and heart development.  

应用多尺度三维图搜索的SD-OCT图像层分割方法

频谱域光学相干层析技术(SD-OCT)是一种广泛应用于眼科领域的成像技术,视网膜组织层分割对视网膜疾病诊断起着至关重要的作用。传统的三维图搜索方法能够同时分割k(k≥1)个三维面,但其存在时间复杂度高、分割病变图像鲁棒性弱等问题。在传统三维图搜索模型的基础上引入多尺度思想,提出应用多尺度三维图搜索的SD-OCT视网膜图像分割方法。首先根据每个组织层的特点,为每层构造一个合理的顶点权重；然后利用相邻列的最大与最小高度差构造列约束限制,改进表面的平滑约束条件；最后利用低尺度的图像,应用三维图搜索方法进行粗分割,逐步向高一尺度应用三维图搜索方法进行单表面细分割。使用改进算法对3组正常眼睛及1组老年黄斑变性视网膜图像进行分割,并将结果与手动分割及传统三维图搜索方法进行比较,实验结果表明,改进算法能够准确有效地分割出3个层边界(边界位置绝对误差是3.86±2.50μm),并且接近于手动分割结果(3.78±2.76μm),优于传统三维图搜索方法(7.92±3.31μm)。