基于数学形态学的新方法在脑组织分割中的应用

针对人体脑部切片图像特点,提出了一种基于数学形态学的脑组织自动分割算法.该算法首先通过形态重构获得粗糙的脑组织区域,然后运用腐蚀和膨胀运算进行边界定位分割出了脑组织,最后对连续断层图像的分割结果进行了三维重建.结果表明该算法分割准确且自动化程度高,适合于大量序列切片图像的快速自动分割.     

An automatic segmentation algorithm for 3D cell cluster splitting using volumetric confocal images

With the rapid advance of three-dimensional (3D) confocal imaging technology, more and more 3D cellular images will be available. Segmentation of intact cells is a critical task in automated image analysis and quantification of cellular microscopic images. One of the major complications in the automatic segmentation of cellular images arises due to the fact that cells are often closely clustered. Several algorithms are proposed for segmenting cell clusters but most of them are 2D based. In other words, these algorithms are designed to segment 2D cell clusters from a single image. Given 2D segmentation methods developed, they can certainly be applied to each image slice with the 3D cellular volume to obtain the segmented cell clusters. Apparently, in such case, the 3D depth information with the volumetric images is not really used. Often, 3D reconstruction is conducted after the individualized segmentation to build the 3D cellular models from segmented 2D cellular contours. Such 2D native process is not appropriate as stacking of individually segmented 2D cells or nuclei do not necessarily form the correct and complete 3D cells or nuclei in 3D. This paper proposes a novel and efficient 3D cluster splitting algorithm based on concavity analysis and interslice spatial coherence. We have taken the advantage of using the 3D boundary points detected using higher order statistics as an input contour for performing the 3D cluster splitting algorithm. The idea is to separate the touching or overlapping cells or nuclei in a 3D native way. Experimental results show the efficiency of our algorithm for 3D microscopic cellular images.     

Dense nuclei segmentation based on graph cut and convexity–concavity analysis

With the rapid advancement of 3D confocal imaging technology, more and more 3D cellular images will be available. However, robust and automatic extraction of nuclei shape may be hindered by a highly cluttered environment, as for example, in fly eye tissues. In this paper, we present a novel and efficient nuclei segmentation algorithm based on the combination of graph cut and convex shape assumption. The main characteristic of the algorithm is that it segments nuclei foreground using a graph‐cut algorithm with our proposed new initialization method and splits overlapping or touching cell nuclei by simple convexity and concavity analysis. Experimental results show that the proposed algorithm can segment complicated nuclei clumps effectively in our fluorescent fruit fly eye images. Evaluation on a public hand‐labelled 2D benchmark demonstrates substantial quantitative improvement over other methods. For example, the proposed method achieves a 3.2 Hausdorff distance decrease and a 1.8 decrease in the merged nuclei error per slice.     

基于锥束CT切片图像的复杂零件三维表面重构

根据锥束CT切片图像的特点，提出了一种面向复杂零件的三维表面重构新方法：首先采用3D亚体素边缘检测算法提取序列切片图像的高精度封闭轮廓，并重构出切片轮廓的拓扑信息，然后采用一种改进的基于截面属性的轮廓分割算法得到若干组局部结构轮廓集，最后对这些轮廓集进行叠加与拼合，形成零件的整个三维表面。实验结果表明，该方法分割轮廓准确，稳定性好，对具有复杂内外结构的零件，可确保其重构结果的拓扑正确性。     

Segmentation of confocal microscope images of cell nuclei in thick tissue sections

Segmentation of intact cell nuclei from three-dimensional (3D) images of thick tissue sections is an important basic capability necessary for many biological research studies. However, segmentation is often difficult because of the tight clustering of nuclei in many specimen types. We present a 3D segmentation approach that combines the recognition capabilities of the human visual system with the efficiency of automatic image analysis algorithms. The approach first uses automatic algorithms to separate the 3D image into regions of fluorescence-stained nuclei and unstained background. This includes a novel step, based on the Hough transform and an automatic focusing algorithm to estimate the size of nuclei. Then, using an interactive display, each nuclear region is shown to the analyst, who classifies it as either an individual nucleus, a cluster of multiple nuclei, partial nucleus or debris. Next, automatic image analysis based on morphological reconstruction and the watershed algorithm divides clusters into smaller objects, which are reclassified by the analyst. Once no more clusters remain, the analyst indicates which partial nuclei should be joined to form complete nuclei. The approach was assessed by calculating the fraction of correctly segmented nuclei for a variety of tissue types: Caenorhabditis elegans embryos (839 correct out of a total of 848), normal human skin (343/362), benign human breast tissue (492/525), a human breast cancer cell line grown as a xenograft in mice (425/479) and invasive human breast carcinoma (260/335). Furthermore, due to the analyst's involvement in the segmentation process, it is always known which nuclei in a population are correctly segmented and which not, assuming that the analyst's visual judgement is correct.     

Quadric segmentation and fitting of data captured by a laser profile scanner mounted on an industrial robot

Applications like geometric reverse engineering, robot vision and automatic inspection require sets of points to be measured from the surfaces of objects and then processed by segmentation and fitting algorithms to establish shape parameters of interest. In industrial applications where speed, reliability and automatic operation is of interest a measuring system based on a laser profile scanner mounted on an industrial robot can be of interest. In earlier publications we have presented such a system and also a segmentation algorithm for planar surfaces using 2D profile data in combination with robot poses. Due to the data reduction offered by this approach the segmentation algorithm computes faster than algorithms based on 3D point sets alone. Encouraged by the results we have now developed a segmentation algorithm for two different quadric surfaces also based on 2D profiles in combination with robot poses. This paper presents the new algorithm together with test results and also an interesting observation that points to future work.     

基于调制度分割的物体轮廓有效测量区域自动识别方法

提出了采用调制度阈值分割技术进行物体轮廓有效测量区域自动识别的一种新方法,克服了投射条纹三维测量技术中由于阴影、条纹断裂、局部镜面反射、暗背景、采样不足以及外来的噪声等因素,使得被测物体表面存在无效测量区域(相位数据不可靠区域)的问题.采用了时域相位去包裹技术,保证了无效区域的相位数据不会影响到有效测量区域的相位数据.与有效测量区域相比,无效区域的调制度明显较低,对调制度直方图进行分析,借鉴图像分割的思想,采用了迭代算法自动求解最佳阈值,辨识物体轮廓测量的有效测量区域和无效测量区域,实现了单视角测量的自动化过程.车灯反射体测量实验证明了这种方法的优越性和可靠性.     

Three-dimensional surface texture visualization of bone tissue through epifluorescence-based serial block face imaging

Serial block face imaging is a microscopy technique in which the top of a specimen is cut or ground away and a mosaic of images is collected of the newly revealed cross-section. Images collected from each slice are then digitally stacked to achieve 3D images. The development of fully automated image acquisition devices has made serial block face imaging more attractive by greatly reducing labour requirements. The technique is particularly attractive for studies of biological activity within cancellous bone as it has the capability of achieving direct, automated measures of biological and morphological traits and their associations with one another. When used with fluorescence microscopy, serial block face imaging has the potential to achieve 3D images of tissue as well as fluorescent markers of biological activity. Epifluorescence-based serial block face imaging presents a number of unique challenges for visualizing bone specimens due to noise generated by sub-surface signal and local variations in tissue autofluorescence. Here we present techniques for processing serial block face images of trabecular bone using a combination of non-uniform illumination correction, precise tiling of the mosaic in each cross-section, cross-section alignment for vertical stacking, removal of sub-surface signal and segmentation. The resulting techniques allow examination of bone surface texture that will enable 3D quantitative measures of biological processes in cancellous bone biopsies.     

三维内部构造显微镜设计

通过连续切片获取生物体二维断层图像然后进行三维重建日益成为生物医学中研究生物体内部三维立体结构的主要途径.在对显微镜用薄片切片机结构及三维重建技术的研究的基础上,本文提出了三维内部构造显微镜的设计方案,解决了生物切片过程中的样品定位、样品切削、断层图像采集、系统控制诸多问题.以本系统获得的二维断层图像为原始数据,利用自行设计三维重建软件,得到了真彩的表面重建和任意切面重建结果.     

基于局部基面参数化的点云数据边界自动提取

提出了一种反求工程中基于局部基面参数化方法的点云数据边界特征的自动提取方法。首先选择合适的局部基面 ,然后用点云垂直投影于局部基面投影点的参数化代替空间点的参数化 ,二次参数曲面逼近点云 ,再利用曲面的微分特性估计点云数据的曲率值 ,求出曲率极值点 ,从中提取边界点。通过这些边界点可以进一步拟合边界曲线 ,达到对点云数据进行自动分片的目的。该方法具有较强的可操作性和实用性 ,对于反求工程的自动化和智能化研究具有实际意义     

Extraction and parametrization of grain boundary networks in glacier ice,using a dedicated method of automatic image analysis

Microstructure analysis of polar ice cores is vital to understand the processes controlling the flow of polar ice on the microscale. This paper presents an automatic image processing framework for extraction and parametrization of grain boundary networks from images of the NEEM deep ice core. As cross‐section images are acquired using controlled surface sublimation, grain boundaries and air inclusions appear dark, whereas the inside of grains appears grey. The initial segmentation step of the software is to separate possible boundaries of grains and air inclusions from background. A Machine learning approach is utilized to gain automatic, reliable classification, which is required for processing large data sets along deep ice cores. The second step is to compose the perimeter of section profiles of grains by planar sections of the grain surface between triple points. Ultimately, grain areas, grain boundaries and triple junctions of the later are diversely parametrized. High resolution is achieved, so that small grain sizes and local curvatures of grain boundaries can systematically be investigated.     

复杂形状刀具数控磨削的3维仿真

对复杂形状刀具数控磨削过程进行3维仿真是研究复杂形状刀具数控磨削过程的有效手段。以Matlab为平台,借助其强大的图形处理功能,通过图像边界识别的方法获得3维特体的截面形状数据,从而实现对复杂形状刀具的数控磨削过程的3维仿真。     

Automatic segmentation of diatom images for classification

A general framework for automatic segmentation of diatom images is presented. This segmentation is a critical first step in contour-based methods for automatic identification of diatoms by computerized image analysis. We review existing results, adapt popular segmentation methods to this difficult problem, and finally develop a method that substantially improves existing results. This method is based on the watershed segmentation from mathematical morphology, and belongs to the class of hybrid segmentation techniques. The novelty of the method is the use of connected operators for the computation and selection of markers, a critical ingredient in the watershed method to avoid over-segmentation. All methods considered were used to extract binary contours from a large database of diatom images, and the quality of the contours was evaluated both visually and based on identification performance.     

Effect of slice thickness on the profile accuracy of model maker rapid prototyping measured by a circular triangulation laser probe

The objective of this research is to investigate the effect of slice thickness on the profile accuracy of the model maker (MM) rapid prototyping (RP) system, layer by layer, through non-contact laser probe measurement. A circular triangulation laser probe, model OTM-3A20, made by Wolf & Beck Co., was mounted on a coordinate measuring machine (CMM), as the non-contact sensor. An adjustment device for the laser probe was designed to minimise the cosine error caused by assembly inaccuracy. The alignment test of the measuring laser beam was carried out using a calibrated specimen. The systematic accuracy of the circular triangulation laser probe with respect to the surface roughness and the surface slope of the RP workpiece was investigated using a HP5529A laser interferometer system. The maximum error of 21/2D RP part profile accuracy can be improved from 220 μm to 131 μm, and the average error can be improved from 78 μm to 46 μm as the slice thickness changed from 0.127 mm (0.005 in.) to 0.0127 μm (0.0005 in). However, the machining time increases by about seven fold based on the experimental results. An overall error of 197 μm as measured by the laser probe is attainable using the finest slice thickness 0.0127 mm (0.0005 in.) for the 3D profile accuracy. To verify the accuracy of non-contact laser probe measurement, the 3D profile of the RP part was also measured by a CNC CMM, with good consistency.     

Automatic deformable registration of histological slides to μCT volume data

Localizing a histological section in the three‐dimensional dataset of a different imaging modality is a challenging 2D‐3D registration problem. In the literature, several approaches have been proposed to solve this problem; however, they cannot be considered as fully automatic. Recently, we developed an automatic algorithm that could successfully find the position of a histological section in a micro computed tomography (μCT) volume. For the majority of the datasets, the result of localization corresponded to the manual results. However, for some datasets, the matching μCT slice was off the ground‐truth position. Furthermore, elastic distortions, due to histological preparation, could not be accounted for in this framework. In the current study, we introduce two optimization frameworks based on normalized mutual information, which enabled us to accurately register histology slides to volume data. The rigid approach allocated 81 % of histological sections with a median position error of 8.4 μm in jaw bone datasets, and the deformable approach improved registration by 33 μm with respect to the median distance error for four histological slides in the cerebellum dataset.     

复杂曲面三坐标数字化磁粒光整加工控制系统

详细介绍了三坐标磁粒光整加工控制系统的软硬件结构、复杂曲面的数字化测量和自动编程方法。该加工控制系统集复杂曲面的数字化、自动编程和三坐标数控加工功能为一体,是结合国际上先进的磁粒光整加工、三坐标数字化测量和三坐标数控技术研制而成的。该系统的研制成功,为实现模具复杂形面的自动高精度光整加工提供了条件。     

基于视觉显著性的无监督海面舰船检测与识别

在航天航空光学遥感舰船目标检测中,受大气、光照、云雾和海岛等海面不确定条件的影响,传统的舰船检测方法存在检测效率低和可靠性差等问题,因此,本文提出一种无监督海面舰船目标自动检测方法。该方法以视觉显著性为依据,结合多显著性检测模型快速搜索海面目标,生成显著图后对其进行粗分割,对提取的目标切片做标记并进行精细分割,利用改进的Hough变换旋转目标主轴以保证目标对Y轴的对称性;对可能检测到的厚重云层和岛屿等伪目标使用梯度方向特征进行鉴别,通过判定目标在360°范围内8个区间的梯度幅度统计值,确认舰船目标及去除伪目标。实验结果表明,该舰船检测方法能够成功提取海面上大小不同,位置随机分布的舰船目标,准确获取舰船目标的数量和位置信息,在大量真实光学遥感图像上的测试结果显示,本文方法检测准确率高于93%,通过目标鉴别处理,剔除伪目标后,虚警率可低于4%,鲁棒性较强。     

采用深度级联卷积神经网络的三维点云识别与分割

三维目标识别和模型语义分割在自动驾驶、机器人导航、3D打印和智能交通等领域均有着广泛应用。针对PointNet++未能结合三维模型的上下文几何结构信息的问题,提出一种采用深度级联卷积神经网络的三维点云识别与分割方法。首先,通过构建深度动态图卷积神经网络捕捉点云的深层语义几何特征;其次,通过将深度动态图卷积神经网络作为深度级联卷积神经网络的子网络递归地应用于输入点集的嵌套分区,以充分挖掘三维模型的深层细粒度几何特征;最后,针对点集特征学习中的点云采样不均匀问题,构建一种密度自适应层,利用循环神经网络编码每个采样点的多尺度邻域特征以捕捉上下文细粒度几何特征。实验结果表明,本算法在三维目标识别数据集ModelNet40和MoelNet10上的识别准确率分别为91.9%和94.3%,在语义分割数据集ShapeNet Part,S3DIS和vKITTI上的平均交并比分别为85.6%,58.3%和38.6%。该算法能够提高三维点云目标识别和模型语义分割的准确率,且具有较高的鲁棒性。     

基于样条曲面描述的大变形有限元数值模拟关键技术探索

模具型腔描述、锻件有限元网格划分、界面接触约束是制约三维复杂体成形有限元数值模拟技术应用的3个关键性问题。以3次B样条曲面描述为基础,对三维复杂工具表面离散、变形体三维网格自动划分、变形体边界节点与模具接触状态判断的一体化技术进行了研究。利用B样条曲面的直观性、局部性、通用性、造型灵活性等特点,构造复杂模具型腔曲面及变形体边界,提出三维网格样条生成法、改进的分块样条生成法及接触判断的区域层次搜索技术。