The application of percolation theory to the compaction of pharmaceutical powders

Based on the concepts of percolation theory the compaction process is interpreted as a site-bond percolation phenomenon. The combination of the Heckel equation with an equation derived earlier yields a simple relationship between the tensile strength σ_t, or the deformation hardness P and the relative density. This mathematical model is identical with the fundamental law of percolation theory i.e., X = s(p − p_c)^q with X= system property equivalent to tensile strength or deformation hardness, S = scaling factor, p = site occupation or bond formation probability corresponding to the relative density p,p_c = percolation threshold and critical exponent q = 1 according to percolation on a Bethe lattice. In the case of the tensile strength σ_t and the deformation hardness p, two percolation thresholds p_c(1) and p_c(2) corresponding to p_c(1) and p_c(2) could be identified. The relative density p_c(1) which is close to the relative poured or relative tapped density can be interpreted as a bond percolation threshold. The particles are bonded by weak interparticulate forces and form only loose compacts as used for filling of capsules. The relative density p_c(2) is the relative density where the first stable pharmaceutical compact is achieved which can no longer be disintegrated mechanically into its primary particles. It is of special interest that the above equation is also valid for the elastic modulus with the only percolation threshold p_c(1) = p_c(1).     

混合遗传算法在医学图像配准中的应用

针对遗传算法和梯度算法各自的优点和缺陷,提出了遗传算法和梯度算法相结合的松散耦合和紧密耦合两种混合遗传算法,并利用基于排挤的小生境技术对其性能进行了改进,使其在搜索能力和收敛速度上都有了较大提高。利用此算法成功实现了以互信息为相似性测度的医学图像配准。计算实例结果表明,本算法能够有效克服局部极值的影响,具备较强的抗噪能力,是一个精度高、稳定性好的医学图像配准算法。     

亚像素断层图像配准数据集的建立

目的针对数字化冰冻铣切断层图像的特点,探讨一种实用的高精度图像配准方法,建立基于数字化断层图像的亚像素级配准数据集。方法采用冰冻铣切技术获取成年男性头颈标本的冰冻连续断层图像,在M atlab软件中自动提取定标点图像特征,采用基于2点的刚体变换算法实现图像的自动配准。结果配准后图像定标点与基准配准点的误差小于1个像素,达到亚像素水平。结论采用外定标的图像配准算法可建立亚像素级的配准数据集,定位标记物的准确识别是获得亚像素级配准数据集的保证。     

微机控制的韧带动态力学特性测试系统

本系统是为自动测试人体韧带或类似组织的动态力学特性试验而研制的。在试验时,受控的加载过程和数据采集过程同时进行。系统向韧带试件提供一个快速的匀速可控的拉伸载荷,模拟人体剧烈运动的实况,同时实时采集力和变形的数据。系统还提供对所采集数据的分析手段,从而得到力、变形、应力、应变、弹性模量和变形能等参数之间的关系,并可以图形和文字形式输出。系统亦可将各数据文件转换为其它应用软件包可接受的形式,以便利用标准商品软件包的数据和图象处理能力。系统采用菜单提示的人机对话方式进行监控。     

The effect of automated landmark identification on morphometric analyses

Morphometric analysis of anatomical landmarks allows researchers to identify specific morphological differences between natural populations or experimental groups, but manually identifying landmarks is time‐consuming. We compare manually and automatically generated adult mouse skull landmarks and subsequent morphometric analyses to elucidate how switching from manual to automated landmarking will impact morphometric analysis results for large mouse (Mus musculus) samples (n = 1205) that represent a wide range of ‘normal’ phenotypic variation (62 genotypes). Other studies have suggested that the use of automated landmarking methods is feasible, but this study is the first to compare the utility of current automated approaches to manual landmarking for a large dataset that allows the quantification of intra‐ and inter‐strain variation. With this unique sample, we investigated how switching to a non‐linear image registration‐based automated landmarking method impacts estimated differences in genotype mean shape and shape variance‐covariance structure. In addition, we tested whether an initial registration of specimen images to genotype‐specific averages improves automatic landmark identification accuracy. Our results indicated that automated landmark placement was significantly different than manual landmark placement but that estimated skull shape covariation was correlated across methods. The addition of a preliminary genotype‐specific registration step as part of a two‐level procedure did not substantially improve on the accuracy of one‐level automatic landmark placement. The landmarks with the lowest automatic landmark accuracy are found in locations with poor image registration alignment. The most serious outliers within morphometric analysis of automated landmarks displayed instances of stochastic image registration error that are likely representative of errors common when applying image registration methods to micro‐computed tomography datasets that were initially collected with manual landmarking in mind. Additional efforts during specimen preparation and image acquisition can help reduce the number of registration errors and improve registration results. A reduction in skull shape variance estimates were noted for automated landmarking methods compared with manual landmarking. This partially reflects an underestimation of more extreme genotype shapes and loss of biological signal, but largely represents the fact that automated methods do not suffer from intra‐observer landmarking error. For appropriate samples and research questions, our image registration‐based automated landmarking method can eliminate the time required for manual landmarking and have a similar power to identify shape differences between inbred mouse genotypes.     

基于自由变形法的多模态医学图像的配准与融合

本研究提出了一种自动识别颈部PET-CT图像特征点的算法，它应用自由变形（FFD）方法以CT图像的特征点为参考使PET图像产生变形，再结合最大互信息法对颈部PET与CT图像进行非刚体配准，最后用改进的小波图像融合法把两者进行融合得出视觉效果比较理想的融合图像。经实际计算得出的变形PET图像与对应CT图像的互信息量大于原始PET图像，并且最后用改进的小波图像融合法得出的融合图像的信息量比一般小波融合大，由此证明本研究所用方法是有效的。     

Standard atlas space for C57BL/6J neonatal mouse brain

A standard atlas space with stereotaxic co-ordinates for the postnatal day 0 (P0) C57BL/6J mouse brain was constructed from the average of eight individual co-registered MR image volumes. Accuracy of registration and morphometric variations in structures between subjects were analyzed statistically. We also applied this atlas coordinate system to data acquired using different imaging protocols as well as to a high-resolution histological atlas obtained from separate animals. Mapping accuracy in the atlas space was examined to determine the applicability of this atlas framework. The results show that the atlas space defined here provides a stable framework for image registration for P0 normal mouse brains. With an appropriate feature-based co-registration strategy, the probability atlas can also provide an accurate anatomical map for images acquired using invasive imaging methods. The atlas templates and the probability map of the anatomical labels are available at .     

Comparison of couples referred and not referred for genetic counseling in a genetic clinic after the birth of a child with a congenital anomaly: A study in a population in the northeastern Netherlands

After the birth of a child with a congenital anomaly, parents have many questions about cause, prognosis, and recurrence risk. An important means of transmitting such information is referral to a genetic clinic. We were interested in knowing what determines whether or not parents are referred for genetic counseling. Data from the local registration of congenital anomalies in the northeastern Netherlands (birth years 1981–1986; 1,217 children/fetuses) and data of the local genetic clinic were compared. The parents of 204 cases (16.8%) had been referred for genetic counseling. Of the couples referred, 76% were referred within one year after birth, usually by a pediatrician (48%). Parents of children with a single anomaly, recognized syndrome, or multiple anomalies not recognized as a syndrome were referred in 5%, 43%, and 26% of cases, respectively. Parents of liveborn children who died were referred in 38% of cases, parents of liveborn/still-alive and stillborn children in 13% and 22%, respectively. Previous affected sibs and absence of previous livebirths increased the likelihood of referral.     

基于互信息的医学图像配准实验

基于互信息的配准方法，包括互信息和归一化互信息方法，是目前医学图像配准中无创、自动且精度很高的一种方法。已经被广泛应用。但是在其目标函数中存在着一定程度的幅值振荡现象。特别是在单模态图像配准中。我们研究发现，产生这种振荡的原因除了插值赝像外，还有由配准过程中图像重叠部分发生变化而引起的熵的变化不确定性。由插值赝像所带来的振荡基本上可以被消除掉；由熵的变化不确定性所带来的振荡很难被消除，但是这种振荡作用在归一化互信息中影响不大。归一化互信息比互信息具有更高的稳健性，适合于更广的应用范围。     

心脏灌注磁共振成像的图像配准

医学时序图像的配准是医学图像分析诊断的基础，也是图像融合等图像处理需要先行解决的问题。本研究提出了一种新的基于图像分割和相关法的算法，用于准确、快速实现心脏灌注核磁共振成像(MRI)图像的配准。该方法以图像相关系数为目标函数，利用迭代运算确定心脏图像的水平位移、垂直位移和旋转角度等参数。该算法优点在于充分考虑了心肌灌注图像的特殊性以及被测对象的身体物理运动、生理运动。结果表明，此方法能有效地对心脏灌注磁共振图像进行配准处理。