Automated analysis of nerve-cell images using active contour models

The number of nerve fibers (axons) in a nerve, the axon size, and shape can all be important neuroanatomical features in understanding different aspects of nerves in the brain. However, the number of axons in a nerve is typically in the order of tens of thousands and a study of a particular aspect of the nerve often involves many nerves. Potentially meaningful studies are often prohibited by the huge number involved when manual measurements have to be employed. A method that automates the analysis of axons from electron-micrographic images is presented. It begins with a rough identification of all the axon centers by use of an elliptical Hough transform procedure. Boundaries of each axons are then extracted based on active contour model, or snakes, approach where physical properties of the axons and the given image data are used in an optimization scheme to guide the snakes to converge to axon boundaries for accurate sheath measurement. However, false axon detection is still common due to poor image quality and the presence of other irrelevant cell features, thus a conflict resolution scheme is developed to eliminate false axons to further improve the performance of detection. The developed method has been tested on a number of nerve images and its results are presented.     

Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search

Current techniques for segmenting macular optical coherence tomography (OCT) images have been 2-D in nature. Furthermore, commercially available OCT systems have only focused on segmenting a single layer of the retina, even though each intraretinal layer may be affected differently by disease. We report an automated approach for segmenting (anisotropic) 3-D macular OCT scans into five layers. Each macular OCT dataset consisted of six linear radial scans centered at the fovea. The six surfaces defining the five layers were identified on each 3-D composite image by transforming the segmentation task into that of finding a minimum-cost closed set in a geometric graph constructed from edge/regional information and a priori determined surface smoothness and interaction constraints. The method was applied to the macular OCT scans of 12 patients (24 3-D composite image datasets) with unilateral anterior ischemic optic neuropathy (AION). Using the average of three experts' tracings as a reference standard resulted in an overall mean unsigned border positioning error of 6.1 $pm$ 2.9 $mu$m, a result comparable to the interobserver variability (6.9 $pm$ 3.3 $mu$m). Our quantitative analysis of the automated segmentation results from AION subject data revealed that the inner retinal layer thickness for the affected eye was 24.1 $mu$m (21%) smaller on average than for the unaffected eye $(p≪0.001)$, supporting the need for segmenting the layers separately.      

采用频域光延迟线的光学相干层析成像

频域光延迟线是一种光学扫描结构,其基本组成是一个衍射光栅、一个透镜和一个扫描镜.把频域光延迟线应用到光学相干层析成像系统中,可以使参考臂扫描速率至少达到数m/s以上,从而实现视频速率的图像获取.从几何光学的角度分析了频域光延迟线的工作原理,分析结果表明在扫描角很小的情况下,入射光的光程或相位变化频率与扫描角频率有较好的线性关系.基于这一结构的光学相干层析成像的结果证明可以避免活体生物组织位移引入的图像模糊.另外,还提出了一种基于微执行器的新扫描装置.     

全光纤光学相干层析系统用于人造指纹的识别

目前商用指纹识别系统由于仅依赖于手指表面二 维图像的脊模式和细节特征进行识别,对人造 指纹有极大的安全漏洞。本文提出一种利用光学相干层析(OCT)技术识别 人造指纹的方法。在分析OCT系统原理及皮肤光学特性的基础上,使用研制的全光纤OCT系 统分别对 人体手指以及被商用指纹识别系统识别通过的人造指模进行成像,获得了二者的二维OCT图 像和对应的一 维信号,同时获得人造指模的三维OCT图像,通过对比分析二者深度方向 上的微结构信息 以及光学特性可以准确地识别出人造指模。实验结果表明,OCT技术不仅可以用于指纹的防 伪,有效地提高生物特征识别系统的安全性能,而且还具有用于指纹识别的潜力。     

Retinal thickness measurements from optical coherence tomography using a Markov boundary model

We present a system for detecting retinal boundaries in optical coherence tomography (OCT) B-scans. OCT is a relatively new imaging modality giving cross-sectional images that are qualitatively similar to ultrasound. However, the axial resolution with OCT is much higher, on the order of 10 microm. Objective, quantitative measures of retinal thickness may be made from OCT images. Knowledge of retinal thickness is important in the evaluation and treatment of many ocular diseases. The boundary-detection system presented here uses a one-dimensional edge-detection kernel to yield edge primitives. These edge primitives are rated, selected, and organized to form a coherent boundary structure by use of a Markov model of retinal boundaries as detected by OCT. Qualitatively, the boundaries detected by the automated system generally agreed extremely well with the true retinal structure for the vast majority of OCT images. Only one of the 1450 evaluation images caused the algorithm to fail. A quantitative evaluation of the retinal boundaries was performed as well, using the clinical application of automatic retinal thickness determination. Retinal thickness measurements derived from the algorithm's results were compared with thickness measurements from manually corrected boundaries for 1450 test images. The algorithm's thickness measurements over a 1-mm region near the fovea differed from the corrected thickness measurements by less than 10 microm for 74% of the images and by less than 25 microm (10% of normal retinal thickness) for 98.4% of the images. These errors are near the machine's resolution limit and still well below clinical significance. Current, standard clinical practice involves a qualitative, visual assessment of retinal thickness. A robust, quantitatively accurate system such as ours can be expected to improve patient care.     

光学相干层析成像用于微机电系统测量研究

为了对硅V型槽的结构进行测量,采用热光源谱域光学相干层析成像法,进行了理论分析和实验验证,取得了硅V型槽的1维深度和2维层析图像,获得了硅V型槽的深度、上部宽度和底部宽度数据分别为145.38m,212m和32m。结果表明,该测量结果与扫描电子显微镜测量值基本一致。这对微机电系统结构测量是有帮助的。     

光学相干层析成像技术的应用

介绍了光学相干层析成像技术在不同领域的应用,预言了未来的发展趋势。     

Multiple contour extraction from graylevel images using an artificial neural network.

For active contour modeling (ACM), we propose a novel self-organizing map (SOM)-based approach, called the batch-SOM (BSOM), that attempts to integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contours from images. We employ feature points, in the form of an edge-map (as obtained from a standard edge-detection operation), to guide the contour (as in the case of SOM-based ACMs) along with the gradient and intensity variations in a local region to ensure that the contour does not "leak" into the object boundary in case of faulty feature points (weak or broken edges). In contrast with the snake-based ACMs, however, we do not use an explicit energy functional (based on gradient or intensity) for controlling the contour movement. We extend the BSOM to handle extraction of contours of multiple objects, by splitting a single contour into as many subcontours as the objects in the image. The BSOM and its extended version are tested on synthetic binary and gray-level images with both single and multiple objects. We also demonstrate the efficacy of the BSOM on images of objects having both convex and nonconvex boundaries. The results demonstrate the superiority of the BSOM over others. Finally, we analyze the limitations of the BSOM.     

Monitoring osteoarthritis in the rat model using optical coherence tomography

OBJECTIVE: A need exists for an animal model to assess therapeutics for osteoarthritis (OA) without sacrificing the animal. Our goal is to assess the progression of experimentally induced osteoarthritis in the rat knee joint by monitoring articular cartilage thickness, surface abnormalities, and collagen organization using a new technology known as optical coherence tomography (OCT). DESIGN: OA was generated in Wistar Hanover rats via injection of sodium iodoacetate into the left articular joint of the knee while normal saline was injected as a control in the contralateral right knee. Rats were sacrificed at 1-, 2-, 3-, 4-, and 8-week intervals and the knee joints were subsequently harvested and imaged using normal and polarization sensitive OCT (PS-OCT). Treated knees were compared to normal counterparts in the contralateral leg. Following imaging, knees underwent both routine histological processing and picrosirus staining for organized collagen. RESULTS: OCT images indicate that injection of sodium iodoacetate resulted in a progressive decrease in cartilage thickness and loss of the bone-cartilage interface which correlated with histology. In addition, PS-OCT was able to detect collagen disorganization, an early indicator of OA. CONCLUSIONS: The use of OCT in combination with the induction of OA in rats is a promising new animal model for assessing articular changes with the goal of monitoring therapeutics longitudinally. Future work will extend the model to in vivo assessments.     

基于主动轮廓模型的红外图像轮廓提取算法

针对主动轮廓模型存在的对初始轮廓位置敏感、凹性目标轮廓无法正确收敛等问题,本文将自适应边缘检测和主动轮廓模型相融合,提出一种改进的红外图像目标轮廓自动提取算法。首先,采用最大类间方差法计算红外图像边缘检测算法的自适应阈值,获取目标初次边缘,降低对初始轮廓位置的敏感性;对初次边缘分别进行横向与纵向填充,填充图像相与运算,对得到目标区域提取二次边缘,将其作为主动轮廓模型的初始轮廓,保证目标凹陷区域轮廓的有效收敛。最后,通过仿真分析验证了该方法能够实现红外目标轮廓的精确自动收敛。     

Characterization of flowing blood optical property under various fibrinogen levels using optical coherence tomography

The feasibility of characterization of human blood fibrinogen levels using optical coherence tomography (OCT) was investigated. Three groups of blood samples were reconstituted of red blood cells: 1) phosphate-buffered saline; 2) plasma with its intrinsic fibrinogen removed and commercial fibrinogen added; and 3) native plasma with various fibrinogen levels (0-12?g/L). OCT signal slope (OCTSS) of blood was extracted from OCT depth-reflectivity profiles. Effects of hematocrit (HCT) and blood flow on OCTSS of the blood under various fibrinogen concentrations were also studied. The results of blood flowing at 5?mm/s showed that OCTSS of all the three groups at HCT of 40% decreases with the increasing fibrinogen concentration up to a certain level, i. e., >8, 6, and 4?g/L for groups 1, 2, and 3, respectively. The blood of group 2 at HCTs of 30%, 40%, and 50% had a rapid decrease in OCTSS in the range of fibrinogen concentration of 0-2, 0-6, and 0-10?g/L, respectively. OCTSS value of blood flowing at 2.5?mm/s was lower than that at 5?mm/s at each fibrinogen concentration. In conclusion, OCTSS has a strong correlation with plasma fibrinogen concentration, and has the potential to identify the abnormal level of human blood fibrinogen.     

Edge location in SAR images: performance of the likelihood ratiofilter and accuracy improvement with an active contour approach

The likelihood ratio edge detector is an efficient filter for the segmentation of synthetic aperture radar (SAR) images. We show that this filter provides biased location of the edge, when the window does not have the same orientation as the edge. A phenomenological model is proposed to characterize this bias. We then introduce an efficient technique to refine edge location: the statistical active contour. The combination of these two methods permits to achieve accurate and regularized edge location.     

Automatic detection of the boundary of the calcaneus fromultrasound parametric images using an active contour model; clinicalassessment

Presents a computerized method for automated detection of the boundary of the os calcis on in vivo ultrasound parametric images, using an active dynamic contour model. The initial contour, defined without user interaction, is an iso-contour extracted from the textural feature space. The contour is deformed through the action of internal and external forces, until stability is reached. The external forces, which characterize image features, are a combination of gray-level information and second-order textural features arising from local cooccurrence matrices. The broadband ultrasound attenuation (BUA) value is then averaged within the contour obtained. The method was applied to 381 clinical images. The contour was correctly detected in the great majority of the cases. For the short-term reproducibility study, the mean coefficient of variation was equal to 1.81% for BUA values and 4.95% for areas in the detected region. Women with osteoporosis had a lower BUA than age-matched controls (p=0.0005). In healthy women, the age-related decline was -0.45 dB/MHz/yr. In the group of healthy post-menopausal women, years since menopause, weight and age were significant predictors of BUA. These results are comparable to those obtained when averaging BUA values in a small region of interest     

Aligning scan acquisition circles in optical coherence tomography images of the retinal nerve fibre layer

Optical coherence tomography (OCT) is widely used in the assessment of retinal nerve fibre layer thickness (RNFLT) in glaucoma. Images are typically acquired with a circular scan around the optic nerve head. Accurate registration of OCT scans is essential for measurement reproducibility and longitudinal examination. This study developed and evaluated a special image registration algorithm to align the location of the OCT scan circles to the vessel features in the retina using probabilistic modelling that was optimised by an expectation-maximization algorithm. Evaluation of the method on 18 patients undergoing large number of scans indicated improved data acquisition and better reproducibility of measured RNFLT when scanning circles were closely matched. The proposed method enables clinicians to consider the RNFLT measurement and its scan circle location on the retina in tandem, reducing RNFLT measurement variability and assisting detection of real change of RNFLT in the longitudinal assessment of glaucoma.     

An active contour method for bone cement reconstruction from C-arm x-ray images

A novel algorithm is presented to segment and reconstruct injected bone cement from a sparse set of X-ray images acquired at arbitrary poses. The sparse X-ray multi-view active contour (SxMAC-pronounced "smack") can 1) reconstruct objects for which the background partially occludes the object in X-ray images, 2) use X-ray images acquired on a noncircular trajectory, and 3) incorporate prior computed tomography (CT) information. The algorithm's inputs are preprocessed X-ray images, their associated pose information, and prior CT, if available. The algorithm initiates automated reconstruction using visual hull computation from a sparse number of X-ray images. It then improves the accuracy of the reconstruction by optimizing a geodesic active contour. Experiments with mathematical phantoms demonstrate improvements over a conventional silhouette based approach, and a cadaver experiment demonstrates SxMAC's ability to reconstruct high contrast bone cement that has been injected into a femur and achieve sub-millimeter accuracy with four images.     

Segmentation of whole cells and cell nuclei from 3-D optical microscope images using dynamic programming

Communications between cells in large part drive tissue development and function, as well as disease-related processes such as tumorigenesis. Understanding the mechanistic bases of these processes necessitates quantifying specific molecules in adjacent cells or cell nuclei of intact tissue. However, a major restriction on such analyses is the lack of an efficient method that correctly segments each object (cell or nucleus) from 3-D images of an intact tissue specimen. We report a highly reliable and accurate semi-automatic algorithmic method for segmenting fluorescence-labeled cells or nuclei from 3-D tissue images. Segmentation begins with semi-automatic, 2-D object delineation in a user-selected plane, using dynamic programming (DP) to locate the border with an accumulated intensity per unit length greater that any other possible border around the same object. Then the two surfaces of the object in planes above and below the selected plane are found using an algorithm that combines DP and combinatorial searching. Following segmentation, any perceived errors can be interactively corrected. Segmentation accuracy is not significantly affected by intermittent labeling of object surfaces, diffuse surfaces, or spurious signals away from surfaces. The unique strength of the segmentation method was demonstrated on a variety of biological tissue samples where all cells, including irregularly shaped cells, were accurately segmented based on visual inspection.     

光学相干层析系统的成像数学模型研究

生物组织样品的光学特性可以由光学相干层析成像系统探测到的后向散射功率确定，文中建立了入射光线在样品介质内的一阶散射数学模型，揭示了样品的衰减系数和后向散射系数与系统探测结果之间的关系。     

应用OCT成像技术对海水珍珠的无损测量研究

为探明两种不同大小的海水珍珠的内部结构差异,利用一种新型扫频光学相干层析（OCT）成像系统和Raman光谱仪,无损分析了中国南珠和南洋珠两类海水珍珠。Raman光谱分析表明,这批海水珍珠主体物相皆为文石,未检测到人工有机染色物和添加物。基于该OCT成像系统的测量和图形处理功能,对这批海水珍珠珠层厚度进行了快速、有效的测量,并根据珠层厚度,将其质量等级分成五等。对比分析了这批海水珍珠样品的厚度与直径,除少数样品外,这批海水珠层厚度与珍珠直径呈弱正相关。此外,通过OCT二维图像的纹理特征,对这批海水珍珠的珍珠层、过渡层、珠核层组织的均匀性等进行了归类和评估。OCT成像技术可为珍珠的珠层厚度和均匀性质量分级提供重要依据。     

光学相干层析成象技术基本原理

本文介绍了光学相干层析成象技术（ＯＣＴ），阐述了层析成象的基本原理，讨论了层析象的信息内容。