基于Kinect的机器人辅助超声扫描系统研究

提出一种采用Kinect传感器作为视觉伺服的机器人辅助超声扫描系统,来规划引导机器人的扫描路线,以实现机器人辅助的超声扫描操作。系统由Kinect传感器、机器人和超声探头组成。采用Kinect实时获取超声探头的RGB图像和深度图像,并计算探头当前位姿,结合坐标系配准结果,得到机器人的位姿信息,再根据术前的机器人轨迹规划,引导机器人的超声扫描路径。开展腿部模型实验验证本系统的可行性,通过对Kinect传感器的相机标定实验,计算得到了RGB相机和深度相机的内外参数,通过对探头上标识物的定位,进而计算出探头当前位姿,结合Kinect与机器人坐标系的配准结果,得到了两者的转换矩阵,并对机器人的位置给出指令,引导机械臂夹持探头到达指定扫描位置。在机器人夹持超声探头扫描过程中,实时计算探头与腿部之间的距离,以保证所采集超声图像的质量及扫描操作的安全性。实验结果表明,在Kinect视觉系统的导航引导下,机器人可以夹持超声探头实现自主超声扫描,以减少超声医师的扫描时间,降低医师的劳动强度。     

Measurement by vertical scanning profilometry of resorption volume and lacunae depth caused by osteoclasts on dentine slices

The resorption pit assay is classically used to evaluate osteoclast activity on bone or dentine slices that can be eroded by these cells. Two different types of cells were generated from peripheral blood mononuclear cells cultured in the presence of M-CSF + sRANKL or with M-CSF + LPS. At the end of the culture period (21 days), cells were discarded and the dentine slices stained with toluidine blue and examined with an NT9100 Wyco vertical scanning profilometer. The images of the dentine surface were corrected for tilt and the eroded volume was calculated on the whole images. The depth of the eroded pits was determined. The data files were used to reconstruct the surface of the slices by standardizing the ground level to compare both conditions. Osteoclasts generated with M-CSF + sRANKL were capable of resorbing a more important volume than those generated with M-CSF + LPS. In addition, the formers were able to resorb the dentine matrix more deeply. Data provided by the microscope were used to reconstruct three-dimensional images of the dentine slices with pseudo colours varying with the depth of erosion. Vertical scanning profilometry, a technique used to measure the roughness of polished or etched surfaces in metallurgic industry, can be used to accurately measure the eroded volume and the mean erosion depth done by osteoclasts in the resorption pit assay.     

Multiphoton fluorescent images with a spatially varying background signal: a ML deconvolution method

By means of multiphoton laser scanning microscopy, neuroscientists can look inside the brain deeper than has ever been possible before. Multiphoton fluorescent images, as all optical images, suffer from degradation caused by a variety of sources (e.g. light dispersion and absorption in the tissue, laser fluctuations, spurious photodetection and staining deficiency). From a modelling perspective, such degradations can be considered the sum of stochastic noise and a background signal. Among the methods proposed in the literature to perform image deconvolution in either confocal or multiphoton fluorescent microscopy, Vicidomini et al. (2009) were the first to incorporate models for noise (a Poisson process) and background signal (spatially constant) in the context of regularized inverse problems. Unfortunately, the so-called split-gradient deconvolution method (SGM) they used did not consider possible spatial variations in the background signal. In this paper, we extend the SGM by adding a maximum-likelihood estimation step for the determination of a spatially varying background signal. We demonstrate that the assumption of a constant background is not always valid in multiphoton laser microscopy and by using synthetic and actual multiphoton fluorescent images, we evaluate the face of validity of the proposed method, and compare its accuracy with the previously introduced SGM algorithm.     

Floc architecture of bioflocculation sediment by ESEM and CLSM

Sediment flocculation is a critical component for the understanding of cohesive sediment dynamics. Traditionally, the referred study has largely been devoted to forming mechanism, influencing factors and physicochemical sediment conditions of all kinds of organic-flocculation and inorganic-flocculation. However, during the last decade, the bioflocculation of sediment by biological activity has been given increasing attention. But most studies have focused on the interrelations between biological and sedimentological variables. With the assistance of a newly developed field kit and correlative microscopy (which includes environmental scanning electron microscopy and confocal laser scanning microscopy), this article begins to bridge the resolution gap between sediment particles and biological activities as well as its metabolic products biofilm, in order to better understand the role of polymeric material biofilm in floc ultrastructure and outward floc behavior of bioflocculation sediment. Results have demonstrated that bioflocculation sediment was observed to be composed of complex networks of biofilm and appeared to be of complicated physical floc structures. The biofilm was found to embed particles and permeate the void space, representing the dominant physical bridging mechanism of the flocs and contributed to the extensive surface area, architecture characteristics, and mechanical properties of bioflocculation sediment.     

A case of Leukonychia with scanning electron microscope observation

Leukonychia is a medical term for white discoloration appearing on nails. The pathophysiologic mechanisms that cause white discoloration are not entirely clear. We processed a case of leukonychia with scanning electron microscope observation and found many crispy, obviously dissociated "layers" in the lower part of the white nail plate. The dissociated "layers" were composed of thick, loose, coarse keratin bundles intertwined with each other. We believe the dissociated "layers" are related to the clinically noted white discoloration appearing on the nails.     

三维颅骨模型获取方法研究

颅面复原是一种对人类的颅骨进行面部容貌复原的技术,该技术以人类学、法医学、解剖学中的头骨与面貌相互关系规律为科学依据,广泛应用于考古、刑侦等领域。其中获取三维颅骨模型是实现复原的第一步,颅骨模型的准确与否会直接影响到将来颅面复原的准确性。文中主要介绍了两种获取三维颅骨模型的方法,一种是对cT图像进行面绘制三维重构,另一种是使用三维扫描仪获取三维颅骨模型。之后对获取的颅骨模型建立法兰克福坐标系。实验表明,通过这两种方法获取的颅骨模型为颅面复原提供了良好的颅骨原始数据。     

网络扫描技术的智能化研究

针对现有网络扫描技术中存在的扫描静态性和分析评估功能有限等不足,在对网络扫描基本原理综合分析的基础上,进行了网络扫描技术智能化策略的分析探讨,同时提出了一个符合智能化策略的网络扫描系统概念模型.     

一种生存性分析系统的设计与实现

针对信息系统生存性分析的概念和几个基本属性的深入研究,根据以往在网络安全领域的研究成果,结合当前实现生存性分析系统的几种不同的设计思路,提出了基于漏洞扫描技术实现生存性分析系统的可行性方案,并详细说明了完成生存性分析系统的分析过程设计.阐述该生存性分析系统实现的软件模块结构和各个模块间的调用关系,建立适合当前计算机处理能力的生存性分析核心计算方法公式,最后给出了这个生存性分析系统的输出结果的例子报表.     

一种自适应振动主动控制策略及其在C型三维表面检测系统中的应用

基干广义最小方差和一步超前预报理论,围绕三维型面扫描系统中所存在的周期性徽振动问题,提出了一种新的自适应振动主动控制算法.以C型臂式三维激光扫描系统为应用背景,基于来自于该系统的数据样本建立了系统的振动动态自回归滑动平均模型(ARMA模型).采用所提出的自适应控制算法对该模型进行了振动主动控制仿真研究.仿真结果验证了所提出的方案可以有效地抑制C型臂运动过程中产生的振动,提高系统的整体三维检测精度.     

Laser range scanner based on self-calibration techniques using coplanarities and metric constraints

In this paper, we propose a novel method to achieve both dense 3D reconstruction of the scene and estimation of the camera intrinsic parameters by using coplanarities and other constraints (e.g., orthogonalities or parallelisms) derived from relations between planes in the scene and reflected curves of line lasers captured by a single camera. In our study, we categorize coplanarities in the scene into two types: implicit coplanarities, which can be observed as reflected curves of line lasers, and explicit coplanarities, which are, for example, observed as walls of a building. By using both types of coplanarities, we can construct simultaneous equations and can solve them up to four degrees of freedom. To upgrade the solution to the Euclidean space and estimate the camera intrinsic parameters, we can use metric constraints such as orthogonalities of the planes. Such metric constraints are given by, for example, observing the corners of rectangular boxes in the scene, or using special laser projecting device composed of two line lasers whose laser planes are configured to be perpendicular.