我们感谢Tanja Maritzen博士和Fabian Feutlinske博士（莱布尼兹德国柏林分子药理学研究所）与我们分享了他们的Fuji ImageJ Clock Scan插件版本，并激励我们开发此版本的程序。我们也非常感谢弗里茨·梅尔切斯博士（Max Planck感染生物学研究所淋巴细胞发育系）对他部门的数据库使用图像进行测试和改进插件的许可。支持:翻译神经科学中心; NIH授权:P30-GM110702-03。

软件安装<ol><li>按照相应网站的推荐安装最新版本的捆绑Java和ImageJ或Fiji ImageJ（请参阅材料表，以获取相应网站的链接）。在下面的文本中，这两个程序都被称为"ImageJ"。 </li><li>使用材料表中提供的链接复制"Clock_Scan-1.0.1。jar"和"Multi_Clock_Scan-1.0.1.jar"插件文件，并将其粘贴到ImageJ插件目录中。或者，使用"插件|安装插件"菜单选项将它们保存在计算机硬盘驱动器上之后安装这些文件。 </li></ol> 2.时钟扫描分析<ol><li> 标准时钟扫描插件（ 图1 ）: <ol><li>使用ImageJ"File | Open"菜单命令打开感兴趣的图像。 </li><li>点击"多边形"工具，或"分割行选择"工具，然后绘制图像以概述整个投资回报率或该区域的一段。有关多边形选择（内部虚线轮廓）的示例，请参见图1A 。 注意:也可以使用软件中提供的其他选择工具（矩形，椭圆形和手绘线选择）。 </li><li>从菜单中选择"插件|时钟扫描"，打开标准时钟扫描协议弹出选项窗口。请注意，此命令还将打开ROI Manager窗口，其大纲自动添加到该窗口。 </li><li>使用插件选项窗口执行以下操作。 <ol><li>检查并更改ROI中心的X和Y坐标（自动计算为物理质量中心的坐标），方法是使用滚动条或更改相应输入框中的值。 见图 1B 。 </li><li>取决于对象sho之外的背景区域的多少扫描时可以覆盖，使用"扫描极限"滚动条调整扫描限制。参见图 1A 。 注意:扫描限制是表示扫描在任何给定方向上超出物体边界超出距离的分数;默认值为1.20，表示扫描长度比扫描方向上物体半径长20％; 见图 1A ，外部虚线）。 </li><li>使用"实际半径"，"减去背景"，"极坐标变换"和/或"带标准偏差的绘图"复选框修改插件的输出。 </li><li>点击"确定"运行插件。 见图1 C-H 。 注意:具有"带标准偏差"和"极坐标变换"或"实际半径"和"极坐标传感器"的协议输出示例选择的"orm"选项分别如图1C和1D以及图 1E和1F所示 ，请注意，计算出的标准偏差（SD）值表示物体的各个径向像素强度扫描之间的变化，还要注意"ROI选择长度"行，显示以像素为单位测量的ROI轮廓长度的信息。 </li></ol></li><li>在生成的"时钟扫描配置文件图"中，使用"列表"命令绘制灰度图像的两个X和Y列数据以及RGB图像的X和四个Y列数据中显示的值，其中Y0， Y1，Y2和Y3列将填充积分和个体（红色，绿色和蓝色）颜色通道像素强度值。 </li></ol></li><li> 多个ROI时钟扫描插件 - 使用多个ROI（ <strongclass ="xfig"&gt;图2 ）: <ol><li>打开包含多个投资回报率的图像。 </li><li>点击"分析|工具|投资回报率管理器"打开ROI管理器。 </li><li>按照轮廓（参见步骤2.1.2），并通过点击ROI Manager窗口中的"添加"将每个ROI添加到ROI管理器中;为图像中的所有ROI执行此操作。如果感兴趣的ROI指标是使用"分析|测量"命令。 <ol><li>有关多个分割线选择的示例，请参见图 2A， 图2为多边形选择示例。 </li></ol></li><li>在"插件"菜单中选择"多时钟扫描"，打开协议选项弹出窗口。 </li><li>使用协议选项窗口执行以下操作。 <ol><li>如果需要，按照步骤2.1.4.2重置扫描限制;默认值为1.20。 </li><li>如果需要，请选择选项离子通过检查"带有标准偏差的绘图"框来绘制具有SD条的平均时钟扫描轮廓。 见图2 C和D。 注意:计算的SD值将表示不同对象的积分时钟扫描配置文件之间的变化。另外，请注意插件窗口中显示"所选ROI数量"信息的行。 </li><li>单击"确定"运行协议。 </li></ol></li><li>在生成的"时钟扫描配置文件图"中，使用"列表"命令绘制"绘图值"窗口中显示的值。请参阅"多时钟扫描配置文件图"窗口图例，用于通过颜色通道进行列标识。 </li><li>请注意，投资回报率是编号的，并且任何给定颜色通道的时钟扫描配置文件按相同的顺序绘制，其中ROI被概述并添加到"投资回报率管理器"中。 </li></ol></li><li> 穆尔tiple ROI时钟扫描插件 - 使用图像堆栈（ 图3 ）: <ol><li>打开一个感兴趣的图像堆栈。 </li><li>点击"分析|工具|投资回报率管理器"打开ROI管理器。 </li><li>概述堆栈中图像的ROI，并将其添加到ROI管理器中，如步骤2.1.2和2.2.3所述。如果感兴趣的ROI指标是使用"分析|测量"命令。 </li><li>在"插件"菜单中选择"多时钟扫描"，打开协议选项弹出窗口。 </li><li>使用协议选项窗口执行以下操作。 <ol><li>如步骤2.1.4.2所述重置扫描限制;默认值为1.20。 </li><li>选择使用SD条绘制平均时钟扫描配置文件的选项，方法是选中"带标准偏差的绘图"框。 注意:计算的SD值将表示在图像状态中选择的对象的不同实例之间的变化CK。另外，请注意插件窗口中的行显示"堆叠中图像数量"的信息。 </li><li>单击"确定"运行协议。 </li></ol></li><li>在"时钟扫描配置文件图"窗口中，单击"列表"，绘制"绘图值"窗口中显示的值，其中Y列编号表示堆栈中的图像位置。 </li></ol></li></ol>

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作者宣称他们没有竞争的经济利益或其他利益冲突。

时钟扫描协议:时钟扫描协议是一种快速简单的图像分析工具。与现有的图像分析方法（例如线性像素强度扫描或ROI的平均像素强度的计算）相比，该协议的优点已经在先前的出版物1,9中进行了详细描述。简而言之，该协议允许通过量化位于与ROI中心不同距离（例如对象的边界）或物体外部的预定位置（背景）的像素的强度来生成整体的径向像素强度分布。由于后者，每个ROI的时钟扫描配置文件可以随时校正其直接背景，这在生物应用中使得该配置文件更少地依赖于本地，样本内或样本到样本之间的非均匀性标签/染色，以及不稳定性显微镜光源的强度或荧光灯曝光次数。时钟扫描配置文件的对象尺寸和形状独立性进一步扩大了该协议的应用范围，通过启用不同对象的比较，以及通过逐点减法"正"和"负"控制的配置文件进行校正对象。 时钟扫描插件:分发和共享原始协议的主要限制是使用Visual Basic 6.0（VB）1,9开发的代码的平台依赖性。这个问题最近由德国莱布尼兹分子药理学研究组织的一个研究小组通过开发出类似的富士ImageJ时钟扫描插件2来解决 。莱布尼茨研究所的插件可以复制原始的时钟扫描基本功能封闭的凸形ROI的粗放射扫描轮廓，此外，它可以处理轮廓线（弧）。但是，由插件生成的配置文件的扫描限制只能设置为100％（对象的边框），这意味着无法量化背景像素强度。此外，它没有能力生成极地变换，在RGB图像中使用不同的颜色通道，或者使用堆叠的图像和处理多个ROI。相比之下，这里描述的两个新的插件完全再现了原始VB代码的功能（ 即 ，产生具有可选的SD显示和/或背景减除的积分时钟扫描像素强度分布，以及处理不同的颜色通道RGB图像）。此外，他们还可以分析片段/弧形ROI（在Leibniz分子药理学研究所2中开发的Fuji ImageJ插件中介绍的功能）。此外，ese插件通过生成ROI尺寸和形状独立的极地ROI图像变换来扩展以前程序的效用，可以在需要图像注册的应用程序中使用。最后，多时钟扫描插件可有效地帮助位于同一图像或图像堆栈中的多个ROI的时钟扫描。程序的后一个新功能在确定与时间和位置相关的更改很重要的应用程序中尤其有用。 限制和故障排除:时钟扫描方法的主要限制是选择凸形ROI的要求。在任何辐射扫描超过一次的ROI轮廓的情况下，时钟扫描轮廓将是无意义的。这将使得相对于从中心到ROI边界的距离的这种径向扫描的长度的归一化是不可能的。另一个限制是时钟扫描配置文件信息是进步的ROI缺乏径向对称性的下降。然而，至少部分地，这两个限制可以通过对复杂形状和不对称ROI的所选段（弧）的分析来克服。在背景区域的部分包含标记的特征的情况下也可以使用片段扫描，这可能会影响背景扣除过程（参见图2A ，用于分析那些不面向其他标记细胞的那些细胞片段的选择示例）。最后，如果需要分析包含3个以上颜色通道的合成图像，则在运行插件之前，应分割这些图像的颜色通道。 未来方向:这些插件功能的未来改进将包括但不限于更新代码以将时钟扫描和多时钟扫描插件的功能结合到一个插件中。彩色协同定位算法（如算法bas根据Pearson相关性或Manders分裂系数的计算），以及插件开发能够处理在图像堆栈中的不同图像或不同切片中选择的多个ROI（当前版本的插件允许分析几个将实现在一个图像内选择的ROI或为堆叠中的所有图像选择的一个ROI）。作者还将感谢插件用户的任何建议，以及使用现有插件时遇到的任何问题的报告。 结论:时钟扫描分析是许多生物学领域成像研究的有前景的工具，从静态细胞标记与各种标记的分析到单个细胞内Na +或Ca ++的扩散研究以及在突触连接的细胞群体中扩散活性（ 例如 ，Ca ++波）的分析10 </11或间隙结耦合单元12 。时钟扫描分析的其他潜在应用领域包括医学图像分析（血管超声图像，CT扫描图像和骨横截面），天文学（螺旋和径向星系成像），化学（从点源扩散），物理学（衍射图案分析），林业（树干环分析确定树龄以及干燥天气和施肥不良），工程（金属管腐蚀）和气候学（气象雷达图像分析）。

这项工作的目标是提供一个无平台的时钟扫描协议，并可免费向任何对这种图像分析感兴趣的研究人员提供。时钟扫描协议最初是在2006年开发的，目的是改进现有的凸型感兴趣区域（ROI）中的像素强度量化方法，一种具有更好的综合能力和改进的空间分辨率的方法。在采集期间，为了测量"背景"像素强度，协议顺序地收集从ROI中心扫描到其边界或ROI外的预定距离的多个径向像素强度分布。协议根据扫描方向测量的单元格半径来缩放这些轮廓。因此，从每个单独径向扫描的中心到ROI边界的距离总是X刻度的100％。最后，程序平均这些个人al轮廓成一个整体的径向像素强度分布。由于缩放，由"时钟扫描"协议产生的平均像素强度分布不依赖于ROI大小，也不在合理的限度内取决于ROI形状。该方法允许直接比较，或者如果需要，可以平均或减去不同ROI的配置文件。该协议还允许通过简单减去位于对象外部的像素的平均强度来校正任何对象的背景噪声的整体像素强度分布。虽然它只在生物样品中进行了测试，但是我们的协议为其他现有的图像分析工具提供了有价值的补充，这些工具用于研究物理或化学过程的图像，这些图像分布在原点附近（如从点源扩散物质） 1 。 然而，原始图像分析方法的主要限制是协议是dev作为Visual Basic 6（VB6）（代码，因此它依赖于平台，难以分发（需要VB6）。为了解决这个问题，并加入了其他调查人员近期的类似工作，我们转换了VB6时钟扫描程序代码转换为两个基于Java的插件，与NIH赞助和免费提供的开源和平台无关的图像分析程序ImageJ 3和Fiji ImageJ 4兼容，此外，这些插件现在有几个新功能可扩展功能的原始协议来处理多个ROI和图像堆栈许多图像分析应用程序不是用户友好的，关于对多个对象进行统计分析，因此通常只显示代表性的数据。通过多时钟扫描ImageJ插件，可以同时促进多个物体的分析，对显微镜数据的鲁棒统计评估，关于单个单元/对象中的信号强度分布，现在可以通过该插件扩展。在这里，我们将描述时钟扫描插件，并在图像分析中显示其应用的示例。

<table><tbody><tr><td>Computer</td><td>Any</td><td></td><td>compatible with software listed below</td></tr><tr><td>ImageJ or Fiji ImageJ</td><td>NIH</td><td>https://imagej.nih.gov/ij/ or https://fiji.sc/</td><td>bundled with Java 1.8 or higher</td></tr><tr><td>Clock-scan plugins</td><td>freeware</td><td>https://sourceforge.net/projects/clockscan/</td><td>Clock_Scan-1.0.1 jar and Multi_Clock_Scan-1.0.1/ jar</td></tr><tr><td>Origin 9.0</td><td>OriginLab</td><td>Northampton, MA, USA</td><td>This program was used to generate some graphs of the original Clock Scan data. Any other graphic software can be used to perform this function</td></tr></tbody></table>

clock scan protocol for image analysis: imagej plugins

用于图像分析的时钟扫描协议是量化在边界内部和外部（背景）在关闭或分段的凸起的感兴趣区域内的平均像素强度的有效工具，导致产生平均的整体径向像素 - 强度分布。该协议最初是在2006年开发的，作为一个视觉基本的6脚本，但是它的分布有限。为了解决这个问题，并加入其他人近期的类似工作，我们将原始的时钟扫描协议代码转换为与NIH赞助和免费提供的图像分析程序（如ImageJ或Fiji ImageJ）兼容的两个基于Java的插件。此外，这些插件具有几个新功能，进一步扩展了原始协议的功能范围，如分析多个感兴趣区域和图像堆栈。程序的后一个特征在确定相关变更很重要的应用中特别有用到时间和位置。因此，生物图像堆叠的时钟扫描分析可能潜在地应用于单个细胞内Na +或Ca ++的扩散，以及对突触群体中扩散活性（ 例如 ，Ca ++波）的分析连接或间隙结耦合电池。在这里，我们将描述这些新的时钟扫描插件，并在图像分析中展示其应用的一些示例。

这里用于说明目的的图像取自我们之前的细胞和组织生物学研究5,6,7和从Allen Mouse Brain Atlas 8中创建的数据库。这两个插件都使用ImageJ 1.50i / Java 1.8.0_77，ImageJ 2.0.0-rc-44 / 1.50e / Java 1.8.9_66和Fiji ImageJ 2.0.0-rc54 / 1.51g / Java 1.8.0_66程序环境成功测试。 图1显示了使用标准时钟扫描插件的图像分析的代表性结果。对于两个插件，时钟扫描过程的基本代码和主要步骤基本上与原始协议1中描述的相同。简单地说，在投资回报率或ROI的一部分在图像上概述之后（ 图1） </strong&gt; A ，内部黄色轮廓）并确定轮廓中心（使用插件选项窗口（自动或手动）; 图 1B ），像素强度的径向扫描从中心到第一个像素的方向开始单元格轮廓，沿着轮廓顺时针方向逐个像素继续（ 图 1A ，分别为直线向量和弯曲的箭头），直到所有的ROI半径被扫描。为了量化ROI背景强度，每个径向扫描的长度可以被设置为超过扫描方向的ROI的半径预设的分数（对于时钟扫描插件的值，默认为0.2或20％的半径） ，外部黄线在图 1A中 ）。然后通过缩放到相应的半径对所收集的径向分布进行对准并平均，以在2中产生积分时钟扫描强度分布56个灰度单位的强度水平（ 图 1C ）。对于RGB图像，除了组合的颜色配置文件外，两个插件都会自动为每个颜色通道（红色，绿色和蓝色的256种强度级别）生成独立的整体径向像素强度分布。 默认情况下，时钟扫描像素强度分布的x尺度表示归一化的ROI半径，100％的刻度表示像素位于ROI的边界（ 图 1C ）。 图 1C所示的轮廓是在选择了"带有标准偏差的曲线"的情况下生成的，因此，该曲线图还显示沿着轮廓X尺度的每个数据点计算的SD。当选择"减去背景"选项时，整个强度分布被校正为背景号码通过逐点减去位于ROI边界和扫描极限边界之间的像素的平均强度（ 图1A中的外部黄线;数据未示出）的逐点减法。如果选择"极性变换"选项，时钟扫描插件将生成一个额外的输出窗口。它包含所选区域的图像的极性变换，包括扫描限制区域，其中在每个径向扫描方向上修改图像，使得从对象的中心到边界的距离总是被标准化为100 ％并由100个像素表示。无论物体的实际尺寸如何，其极坐标变换图像的垂直和水平尺寸都是像素扫描限制的两倍（ 图 1D所示的示例中为240像素×240像素）。最后，选择"实际半径"选项将导致生成时钟扫描以及根据物体的实际平均半径和原始图像的空间校准的单位（分别为图1E和F ）缩放的极坐标变换图像。 图1G和H示出了使用对象尺寸和形状无关的极化变换和集成的ImageJ命令和工具的附加图像分析选项。可能被认为对某些类型的图像分析有用的命令的示例是分段线工具和"Analyze | Plot Profile"命令（ 图1 G ）和"Analyze | Surface Plot"命令（ 图1 H ）。 图2和图3显示了使用多时钟扫描插件的图像分析的代表性结果。的输出多时钟扫描插件由两个图形组成:第一个图形显示所选对象的各个时钟扫描配置文件（ 图2 C ），第二个图形显示这些单独的时钟扫描配置文件的平均值（±SD，可选; 图 2D ） 。 对于RGB图像（ 图 2E），还为每个选定的ROI（ 图2 F ）显示为每个单独颜色通道计算的时钟扫描曲线，并且在所有选定对象的给定通道内计算平均值（ 图2 G ） 。类似地，在执行堆叠的时钟扫描分析之后，显示图像堆栈中的对象的个体和平均时钟扫描配置文件（ 图3A-3D ，平均时钟扫描配置文件未显示）。如前所述，数字使用al数据通过执行绘图"List"命令来生成这些图。 图4说明了时钟扫描插件中极地变换选项的一个附加应用:其适用于图像配准和重叠操作。在该图中，使用ROI大小和形状无关极性变换来比较不同小鼠皮质区域之间表达α3钠/钾-ATP酶泵的神经元的荧光标记分布，图谱显示边界和解剖组织这些区域（ 图4A-4B ）。使用时钟扫描协议，参考（地图集）的注册和这种比较所需的实际图像仅限于对齐图像的简单过程，概述了两个图像中感兴趣的结构，然后生成ROI大小和形状 - 独立的极地变换。在图4所示的实施例中，极性转换的比较清楚地表明了小鼠脑皮层中标记细胞的不均匀分布，其运动皮层，背部部分2/3层的表面区域的密度特别高的神经岛细胞皮质，外侧轨道皮层，以及运动皮层的深层（ 图4C-4D ）。 <img alt="图1" class="xfigimg" src="/files/ftp_upload/55819/55819fig1.jpg" /> 图1 :用于图像分析的时钟扫描插件的应用的代表性示例。 （ A ）针对Na + / K + -ATP酶的α3同种型（α3NKA;对组织加工和染色的细节参见Schneider 等人 ）免疫染色的大鼠背根神经节的一部分的荧光光图像。使用多边形线工具（内部黄线）概述了其中一个用α3NKA（白色）标记的边界的神经元轮廓。如图B（扫描极限滚动条）所示，径向扫描（白色箭头）限制（外部黄色线）被设置为物体半径的120％，从物体中心（白点）到轮廓的第一个像素。 （ B ）时钟扫描插件的主选项窗口的屏幕快照。 （ C ）图A所示的单元的积分像素强度分布图（706个径向扫描剖面的平均值，见B中的轮廓长度;垂直条是SD条）。 （ D ） - 研究的细胞谱的极地变换图像。 （ E ）选择了"实际半径"选项获得的相同单元的时钟扫描配置文件。注意，与C中所示的轮廓不同，该轮廓的x刻度显示实际的空间校准单位（μm）。 （ F ）获得的相同细胞的极性转化<html>选择"实际半径"选项。请注意，此变换的规模现在是实际的空间校准单位（μm）。 （ G ）使用分割线工具（线宽设置为10像素或径向扫描长度的10％）来概述D中所示的极性变换的边界并进行分析。执行"Analyze | Plot Profile"命令来测量沿对象边界的平均标记强度的变化（图中的每个数据点表示选择线宽度上所有像素的平均强度）。 （ H ）将"Analyze | Surface Plot"命令应用于面板D所示的极化变换图像，以创建物体的标记强度的3-D表示。 <a href="http://ecsource.jove.com/files/ftp_upload/55819/55819fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> e 2"class ="xfigimg"src ="/ files / ftp_upload / 55819 / 55819fig2.jpg"/&gt; 图2 :使用多时钟扫描插件进行图像分析的代表性示例应用。 （ A ）在α3NKA免疫染色的大鼠背根神经节部分内捕获了四个视野（参见图1 的传说）。为了简化多时钟扫描插件的使用，将这些图像放置在堆叠中，然后使用"Image | Stacks | Make Montage"命令将其转换为单个图像。红线和数字表示该图像中的五个感兴趣区域的分段线选择。 （ B ）当插件用于分析灰度图像时，将显示多时钟扫描窗口的屏幕截图。 （ C ）面板A中显示的五个ROI的单独时钟扫描配置文件。（ D ）所选ROI的平均时钟扫描配置文件（面板A）使用SD条（选择"选择标准偏差"）。 （ E ）用4,6-二脒基-2-苯基吲哚（DAPI，核染色，蓝色）标记的培养的小鼠preBI-淋巴细胞的RGB图像和用于β1整合素（绿色）和F-肌动蛋白（红色）的荧光标记抗体;参见Dobretsov 等人 7 ，细胞培养技术和Yuryev 等人 11用于染色细节）。使用ImageJ多边形选择工具概述了11个单元格（参见数字标签）。执行"Image | Color | Split Channels"菜单功能后，右侧的面板显示单元格＃7的绿色和红色通道视图（左侧面板上的矩形选择）。 （ F ）单个单元时钟扫描配置文件（复合和红色，绿色和蓝色颜色通道配置文件分别由黑色，红色，绿色和蓝色线显示）。 （ G ）面板中选择的所有11个ROI的平均时钟扫描配置文件E.颜色标识如面板G（在多时钟扫描过程中，不使用标准偏差选项的图形）。 <a href="http://ecsource.jove.com/files/ftp_upload/55819/55819fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图3" class="xfigimg" src="/files/ftp_upload/55819/55819fig3.jpg" /> 图3 :多时钟扫描插件和图像堆栈分析。 （ A ）所选择的蒙太奇和"保存为堆叠"图像帧。在第一帧中示出了用差分干涉对比（DIC）显微镜捕获的背根神经节神经元的图像。使用外照射荧光显微镜获取随后的帧，以在细胞电刺激之前和之后以不同的时间间隔监测细胞内钙浓度。数字旁边的尊敬e图像指示以ms为单位的时间6 。使用堆叠的DIC图像概述细胞的边界（左上框架;星号表示用于记录并用钙敏感染料Oregon Green BAPTA-1（OGB-1）填充细胞的膜片钳移液管） ），然后用于对剩余的图像运行多时钟扫描程序。 （ B ）当程序在一堆图像上运行时，多时钟扫描窗口的屏幕截图。 （ C ）OGB-1荧光信号与细胞中心不同距离（半径的百分比）和电刺激之前和之后不同时间（以毫秒为单位）的时钟扫描曲线。为了准备这些图，使用了专业图形软件。 （ D ）OGB-1信号强度随亚膜和深细胞质细胞区域的时间变化（分别为红色和黑色圆圈和线条）。为了获得这些数据，计算每个数据点的平均值和标准差在面板C（阴影区域）中显示的每个时钟扫描配置的x尺度的20-40％和70-90％之间。 <a href="http://ecsource.jove.com/files/ftp_upload/55819/55819fig3large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图4" class="xfigimg" src="/files/ftp_upload/55819/55819fig4.jpg" /> 图4 :在图像注册和覆盖中使用时钟扫描插件的示例。 （ A和B ）来自冠状切片（Allen Mouse Brain Atlas）的板29的截图和来自明胶嵌入的小鼠脑的200μm厚的振动体部分切割成与图谱图像大致相同的水平。该实施例中使用的转基因小鼠在α3NKA的启动子下表达ZsGreen荧光蛋白，以鉴定表达α3NKA的神经元2 。确定特别富集这些神经元的皮层区域（图B中的图像上的亮点），从具有相同参考点的两个图像（皮质和嗅觉之间的中间边界）开始整理皮质区域（黄色虚线）灯泡;箭头）。 （ C ）面板代表（从左到右）:时钟扫描极坐标转换在鼠标大脑部分（面板B）的图像内的地图集图像（图A）中选择的ROI，并叠加这两个变换图像（"图像| Overlay | Add Image"命令，50％不透明度设置）。 （ D ）与图C中相同的图像，但是使用ImageJ多边形，分割线选择工具和"分析|工具|同步窗口"的两个其他变换图像中概述的主要皮层区域（如图所示）命令。缩写与原始脑图集相同:运动小学和中学（MOp，MO），岛内岛屿，多颈部（AId），眶外侧，腹侧和内侧（ORBI，ORBv1，ORBm），前期（PL），前扣带，背部（ACAd）皮质。 MOs区域中的数字是指主要皮质层，可以在适当的冠状脑水平的小鼠运动皮质中进行区分。 <a href="http://ecsource.jove.com/files/ftp_upload/55819/55819fig4large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>

Watch this Scientific Journal Video about Clock Scan Protocol for Image Analysis: ImageJ Plugins at JoVE.com

Clock Scan Protocol for Image Analysis: ImageJ Plugins

本文介绍了用于"时钟扫描"图像分析的两个新颖的ImageJ插件。这些插件扩展了原始视觉基础6程序的功能，最重要的是，通过将其与ImageJ免费图像分析软件包捆绑在一起，使程序可用于大型研究团体。

用于图像分析的时钟扫描协议:ImageJ插件

The clock scan protocol for image analysis is an efficient tool to quantify the average pixel intensity within, at the border, and outside (background) a ...

clock-scan-protocol-for-image-analysis-imagej-plugins

Nanyang Technological University

Research

JoVE Journal

Biology

17.3K 次观看.  University of Arkansas for Medical Sciences. 本文介绍了用于"时钟扫描"图像分析的两个新颖的ImageJ插件。这些插件扩展了原始视觉基础6程序的功能，最重要的是，通过将其与ImageJ免费图像分析软件包捆绑在一起，使程序可用于大型研究团体。 

视频: Clock Scan Protocol for Image Analysis: ImageJ Plugins

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

A fundamental goal in biology is to understand how patterns emerge during development. Several groups have shown that patterning can be achieved in vitro when stem cells are spatially confined onto micropatterns, thus setting up experimental models which offer unique opportunities to identify, in vitro, the fundamental principles of biological organisation.
Here we describe our own implementation of the methodology. We adapted a photo-patterning technique to reduce the need for specialized equipment to make it easier to establish the method in a standard cell biology laboratory. We also developed a free, open-source and easy to install image analysis framework in order to precisely measure the preferential positioning of sub-populations of cells within colonies of standard shapes and sizes. This method makes it possible to reveal the existence of patterning events even in seemingly disorganized populations of cells. The technique provides quantitative insights and can be used to decouple influences of the environment (e.g., physical cues or endogenous signaling), on a given patterning process.

The method presented here uses micropatterning together with quantitative imaging to reveal spatial organization within mammalian cultures. The technique is easy to establish in a standard cell biology laboratory and offers a tractable system to study patterning in vitro.

使用微模式和定量成像绘制哺乳动物细胞的新兴空间组织图

A fundamental goal in biology is to understand how patterns emerge during development. Several groups have shown that patterning can be achieved in vitro ...

科研

发育生物学

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Micro-computed tomography (micro-CT) is routinely used to assess bone quantity and trabecular microstructural properties in small animals under different bone loss conditions. However, the standard approach for trabecular analysis of micro-CT images is slice-by-slice semi-automatic hand-contouring, which is labor intensive and error prone. Described here is an efficient method for automatic segmentation of trabecular bones according to the bone's outer boundaries, where trabecular bones can be identified and segmented automatically with accuracy with less operator bias when appropriate segmentation parameters are set. To profile satisfactory segmentation parameters, an image stack of segmentation results is displayed, where all possible combinations of the segmentation parameters are changed one by one in sequence, and segmentation results with associated parameters can easily be visually checked. As a quality-control feature of the plugin, simulated standard objects are quantified where the measured quantities can be compared with theoretical values. Layer-by-layer quantification of trabecular properties and trabecular thicknesses are reported by such a plugin, and the distributions of such properties within the selected regions can be profiled easily. Although layer-by-layer quantification retains more information about trabecular bones and facilitates further statistical analysis of structural changes, such measures are unavailable from the output of current commercial software, where only a single quantified value for each parameter is reported for each sample. Therefore, the described workflows are better approaches for analyzing trabecular bones with accuracy and efficiency.

We present a workflow for segmenting and quantifying trabecular bones for 2D and 3D images based on the bone&#39;s outer boundary using an ImageJ plugin. This approach is more efficient and accurate than the current manual hand-contouring approach, and provides layer-by-layer quantifications, which are not available in current commercial software.

用 Imagej 插件对小梁骨的外边界辅助分割和量化

Micro-computed tomography (micro-CT) is routinely used to assess bone quantity and trabecular microstructural properties in small animals under different ...

生物工程

Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro

Particle image velocimetry (PIV) is used in a wide variety of fields, due to the opportunity it provides for precisely visualizing and quantifying flows across a large spatiotemporal range. However, its implementation typically requires the use of expensive and specialized instrumentation, which limits its broader utility. Moreover, within the field of bioengineering, in vitro flow visualization studies are also often further limited by the high cost of commercially sourced tissue phantoms that recapitulate desired anatomical structures, particularly for those that span the mesoscale regime (i.e., submillimeter to millimeter length scales). Herein, we present a simplified experimental protocol developed to address these limitations, the key elements of which include 1) a relatively low-cost method for fabricating mesoscale tissue phantoms using 3-D printing and silicone casting, and 2) an open-source image analysis and processing framework that reduces the demand upon the instrumentation for measuring mesoscale flows (i.e., velocities up to tens of millimeters/second). Collectively, this lowers the barrier to entry for nonexperts, by leveraging resources already at the disposal of many bioengineering researchers. We demonstratethe applicability of this protocol within the context of neurovascular flow characterization; however, it is expected to be relevant to a broader range of mesoscale applications in bioengineering and beyond.

Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro

Here we present simplified methods for fabricating transparent neurovascular phantoms and characterizing the flow therein. We highlight several important parameters and demonstrate their relationship to field accuracy.

神经血管流动的中尺度粒子图像测速研究

Particle image velocimetry (PIV) is used in a wide variety of fields, due to the opportunity it provides for precisely visualizing and quantifying flows ...

ReAsH/FlAsH Labeling and Image Analysis of Tetracysteine Sensor Proteins in Cells

Fluorescent proteins and dyes are essential tools for the study of protein trafficking, localization and function in cells. While fluorescent 
proteins such as green fluorescence protein (GFP) have been extensively used as fusion partners to proteins to track the properties of a protein of interest1, recent 
developments with smaller tags enable new functionalities of proteins to be examined in cells such as conformational change and protein-association 2, 3. One small 
tag system involves a tetracysteine motif (CCXXCC) genetically inserted into a target protein, which binds to biarsenical dyes, ReAsH (red fluorescent) and FlAsH 
(green fluorescent), with high specificity even in live cells 2. The TC/biarsenical dye system offers far less steric constraints to the host protein than 
fluorescent proteins which has enabled several new approaches to measure conformational change and protein-protein interactions 4-7. We recently developed 
a novel application of TC tags as sensors of oligomerization in cells expressing mutant huntingtin, which when mutated aggregates in neurons in Huntington 
disease 7. Huntingtin was tagged with two fluorescent dyes, one a fluorescent protein to track protein location, and the second a TC tag which only 
binds biarsenical dyes in monomers. Hence, changes in colocalization between protein and biarsenical dye reactivity enabled submicroscopic oligomer 
content to be spatially mapped within cells. Here, we describe how to label TC-tagged proteins fused to a fluorescent protein (Cherry, GFP or CFP) 
with FlAsH or ReAsH in live mammalian cells and how to quantify the two color fluorescence (Cherry/FlAsH, CFP/FlAsH or GFP/ReAsH combinations).

The biarsenical dyes FlAsH and ReAsH bind specifically to tetracysteine motifs in proteins and can selectively label proteins in live cells. Recently this labeling strategy has been used to develop sensors for different protein conformations or oligomeric states. We describe the labeling approach and methods to quantitatively analyze binding.

ReAsH / FLASH标签和图像分析Tetracysteine​​传感器蛋白在细胞中

Fluorescent proteins and dyes are essential tools for the study of protein trafficking, localization and function in cells.  While fluorescent 
proteins ...

生物学

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo

In cardiac muscle, intracellular Ca2+ transients activate contractile myofilaments, causing contraction, macroscopic shortening, and geometric&#160;deformation. Our understanding of the internal relationships between these events has been limited because we can neither &#39;see&#39; inside the muscle nor precisely track the spatio-temporal nature of excitation-contraction dynamics. To resolve these problems, we have constructed a device that combines a suite of imaging modalities. Specifically, it integrates a brightfield microscope to measure local changes of sarcomere length and tissue strain, a fluorescence microscope to visualize the Ca2+ transient, and an optical coherence tomograph to capture the tissue&#39;s geometric&#160;changes throughout the time-course of a cardiac cycle. We present here the imaging infrastructure and associated data collection framework. Data are collected from isolated rod-like tissue structures known as trabeculae carneae. In our instrument, a pair of position-controlled platinum hooks hold each end of an ex vivo muscle sample while it is continuously superfused with nutrient-rich saline solution. The hooks are under independent control, permitting real-time control of muscle length and force. Lengthwise translation enables the piecewise scanning of the sample, overcoming limitations associated with the relative size of the microscope imaging window (540 &#181;m by 540 &#181;m) and the length of a typical trabecula (&#62;2000 &#181;m). Platinum electrodes at either end of the muscle chamber stimulate the trabecula at a user-defined rate. We exploit the stimulation signal as a trigger for synchronizing the data from each imaging window to reconstruct the entire sample twitching under steady-state conditions. Applying image-processing techniques to these brightfield imaging data provides tissue displacement and sarcomere length maps. Such a collection of data, when incorporated into an experiment-modeling pipeline, will provide a deeper understanding of muscle contractile homogeneity and heterogeneity in physiology and pathophysiology.

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo

This protocol presents a collection of sarcomere, calcium, and macroscopic geometric&#160;data from an actively contracting cardiac trabecula ex vivo. These simultaneous measurements are made possible by the integration of three imaging modalities.

同时布莱特菲尔德， 荧光， 和光学相干断层成像收缩心脏特拉贝库莱 Ex Vivo

In cardiac muscle, intracellular Ca2+ transients activate contractile myofilaments, causing contraction, macroscopic shortening, and ...

TACI: An ImageJ Plugin for 3D Calcium Imaging Analysis

Research in neuroscience has evolved to use complex imaging and computational tools to extract comprehensive information from data sets. Calcium imaging is a widely used technique that requires sophisticated software to obtain reliable results, but many laboratories struggle to adopt computational methods when updating protocols to meet modern standards. Difficulties arise due to a lack of programming knowledge and paywalls for software. In addition, cells of interest display movements in all directions during calcium imaging. Many approaches have been developed to correct the motion in the lateral (x/y) direction.
This paper describes a workflow using a new ImageJ plugin, TrackMate Analysis of Calcium Imaging (TACI), to examine motion on the z-axis in 3D calcium imaging. This software identifies the maximum fluorescence value from all the z-positions a neuron appears in and uses it to represent the neuron&#39;s intensity at the corresponding t-position. Therefore, this tool can separate neurons overlapping in the lateral (x/y) direction but appearing&#160;on distinct z-planes. As an ImageJ plugin, TACI is a user-friendly, open-source computational tool for 3D calcium imaging analysis. We validated this workflow using fly larval thermosensitive neurons that displayed movements in all directions during temperature fluctuation and a 3D calcium imaging dataset acquired from the fly brain.

TrackMate Analysis of Calcium Imaging (TACI) is an open-source ImageJ plugin for 3D calcium imaging analysis that examines motion on the z-axis and identifies the maximum value of each z-stack to represent a cell's intensity at the corresponding time point. It can separate neurons overlapping in the lateral (x/y) direction but on different z-planes.

TACI:用于 3D 钙成像分析的 ImageJ 插件

Research in neuroscience has evolved to use complex imaging and computational tools to extract comprehensive information from data sets. Calcium imaging ...

神经科学

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

The National Institute of Health&#39;s ImageJ is a powerful, freely available image processing software suite. ImageJ has comprehensive particle analysis algorithms which can be used effectively to count various biological particles. When counting large numbers of cell samples, the hemocytometer presents a bottleneck with regards to time. Likewise, counting membranes from migration/invasion assays with the ImageJ plugin Cell Counter, although accurate, is exceptionally labor intensive, subjective, and infamous for causing wrist pain. To address this need, we developed two plugins within ImageJ for the sole task of automated hemocytometer (or known volume) and migration/invasion cell counting. Both plugins rely on the ability to acquire high quality micrographs with minimal background. They are easy to use and optimized for quick counting and analysis of large sample sizes with built-in analysis tools to help calibration of counts. By combining the core principles of Cell Counter with an automated counting algorithm and post-counting analysis, this greatly increases the ease with which migration assays can be processed without any loss of accuracy.

This paper describes the quantification of hemocytometer and migration/invasion micrographs through two new open-source ImageJ plugins Cell Concentration Calculator and migration assay Counter. Furthermore, it describes image acquisition and calibration protocols as well as discusses in detail the input requirements of the plugins.

自动定量分析细胞计数程序使用ImageJ插件

The National Institute of Health&#39;s ImageJ is a powerful, freely available image processing software suite. ImageJ has comprehensive particle analysis ...

Applications of Spatio-temporal Mapping and Particle Analysis Techniques to Quantify Intracellular Ca2+ Signaling In Situ

Ca2+ imaging of isolated cells or specific types of cells within intact tissues often reveals complex patterns of Ca2+ signaling. This activity requires careful and in-depth analyses and quantification to capture as much information about the underlying events as possible. Spatial, temporal and intensity parameters intrinsic to Ca2+ signals such as frequency, duration, propagation, velocity and amplitude may provide some biological information required for intracellular signalling. High-resolution Ca2+ imaging typically results in the acquisition of large data files that are time consuming to process in terms of translating the imaging information into quantifiable data, and this process can be susceptible to human error and bias. Analysis of Ca2+ signals from cells in situ typically relies on simple intensity measurements from arbitrarily selected regions of interest (ROI) within a field of view (FOV). This approach ignores much of the important signaling information contained in the FOV. Thus, in order to maximize recovery of information from such high-resolution recordings obtained with Ca2+dyes or optogenetic Ca2+ imaging, appropriate spatial and temporal analysis of the Ca2+ signals is required. The protocols outlined in this paper will describe how a high volume of data can be obtained from Ca2+ imaging recordings to facilitate more complete analysis and quantification of Ca2+ signals recorded from cells using a combination of spatiotemporal map (STM)-based analysis and particle-based analysis. The protocols also describe how different patterns of Ca2+ signaling observed in different cell populations in situ can be analyzed appropriately. For illustration, the method will examine Ca2+ signaling in a specialized population of cells in the small intestine, interstitial cells of Cajal (ICC), using GECIs.

Applications of Spatio-temporal Mapping and Particle Analysis Techniques to Quantify Intracellular Ca2+ Signaling In Situ

Genetically encoded Ca2+ indicators (GECIs) have radically changed how in situ Ca2+ imaging is performed. To maximize data recovery from such recordings, appropriate analysis of Ca2+ signals is required. The protocols in this paper facilitate the quantification of Ca2+ signals recorded in situ using spatiotemporal mapping and particle-based analysis.

时空映射和粒子分析技术在细胞内 ca2 +原位信令定量中的应用

Ca2+ imaging of isolated cells or specific types of cells within intact tissues often reveals complex patterns of Ca2+ signaling. This activity requires ...

Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response

Swarming is a form of surface motility observed in many bacterial species including Pseudomonas aeruginosa and Escherichia coli. Here, dense populations of bacteria move over large distances in characteristic tendril-shaped communities over the course of hours. Swarming is sensitive to several factors including medium moisture, humidity, and nutrient content. In addition, the collective stress response, which is observed in P. aeruginosa that are stressed by antibiotics or bacteriophage (phage), repels swarms from approaching the area containing the stress. The methods described here address how to control the critical factors that affect swarming. We introduce a simple method to monitor swarming dynamics and the collective stress response with high temporal resolution using a flatbed document scanner, and describe how to compile and perform a quantitative analysis of swarms. This simple and cost-effective method provides precise and well-controlled quantification of swarming and may be extended to other types of plate-based growth assays and bacterial species.

We detail a simple method to produce high-resolution time-lapse movies of Pseudomonas aeruginosa swarms that respond to bacteriophage (phage) and antibiotic stress using a flatbed document scanner. This procedure is a fast and simple method for monitoring swarming dynamics and may be adapted to study the motility and growth of other bacterial species.

细菌群的延时成像与集体压力反应

Swarming is a form of surface motility observed in many bacterial species including Pseudomonas aeruginosa and Escherichia coli. Here, dense populations ...

Lineage Tracing and Clonal Analysis in Developing Cerebral Cortex Using Mosaic Analysis with Double Markers (MADM)

Beginning from a limited pool of progenitors, the mammalian cerebral cortex forms highly organized functional neural circuits. However, the underlying cellular and molecular mechanisms regulating lineage transitions of neural stem cells (NSCs) and eventual production of neurons and glia in the developing neuroepithelium remains unclear. Methods to trace NSC division patterns and map the lineage of clonally related cells have advanced dramatically. However, many contemporary lineage tracing techniques suffer from the lack of cellular resolution of progeny cell fate, which is essential for deciphering progenitor cell division patterns. Presented is a protocol using mosaic analysis with double markers (MADM) to perform in vivo clonal analysis. MADM concomitantly manipulates individual progenitor cells and visualizes precise division patterns and lineage progression at unprecedented single cell resolution. MADM-based interchromosomal recombination events during the G2-X phase of mitosis, together with temporally inducible CreERT2, provide exact information on the birth dates of clones and their division patterns. Thus, MADM lineage tracing provides unprecedented qualitative and quantitative optical readouts of the proliferation mode of stem cell progenitors at the single cell level. MADM also allows for examination of the mechanisms and functional requirements of candidate genes in NSC lineage progression. This method is unique in that comparative analysis of control and mutant subclones can be performed in the same tissue environment in vivo. Here, the protocol is described in detail, and experimental paradigms to employ MADM for clonal analysis and lineage tracing in the developing cerebral cortex are demonstrated. Importantly, this protocol can be adapted to perform MADM clonal analysis in any murine stem cell niche, as long as the CreERT2 driver is present.

Lineage Tracing and Clonal Analysis in Developing Cerebral Cortex Using Mosaic Analysis with Double Markers MADM

A protocol to perform lineage tracing and functional genetic analysis of candidate genes at a single cell level using mosaic analysis with double markers (MADM) is presented. MADM clonal analysis provides a quantitative framework to measure the proliferative behavior, cellular output, and lineage relationship of individual progenitors and their daughter cells.

使用双标记 （MADM） 的马赛克分析开发脑皮质的血统跟踪和克隆分析

Beginning from a limited pool of progenitors, the mammalian cerebral cortex forms highly organized functional neural circuits. However, the underlying ...

用于图像分析的时钟扫描协议:ImageJ插件

摘要

探索更多视频

此视频中的章节

使用微模式和定量成像绘制哺乳动物细胞的新兴空间组织图

用 Imagej 插件对小梁骨的外边界辅助分割和量化

神经血管流动的中尺度粒子图像测速研究

ReAsH / FLASH标签和图像分析Tetracysteine传感器蛋白在细胞中

同时布莱特菲尔德，荧光，和光学相干断层成像收缩心脏特拉贝库莱 Ex Vivo

TACI:用于 3D 钙成像分析的 ImageJ 插件

自动定量分析细胞计数程序使用ImageJ插件

时空映射和粒子分析技术在细胞内 ca^{2 +}原位信令定量中的应用

细菌群的延时成像与集体压力反应

使用双标记（MADM）的马赛克分析开发脑皮质的血统跟踪和克隆分析

用于图像分析的时钟扫描协议:ImageJ插件

摘要

探索更多视频

此视频中的章节

使用微模式和定量成像绘制哺乳动物细胞的新兴空间组织图

用 Imagej 插件对小梁骨的外边界辅助分割和量化

神经血管流动的中尺度粒子图像测速研究

ReAsH / FLASH标签和图像分析Tetracysteine​​传感器蛋白在细胞中

同时布莱特菲尔德， 荧光， 和光学相干断层成像收缩心脏特拉贝库莱 Ex Vivo

TACI:用于 3D 钙成像分析的 ImageJ 插件

自动定量分析细胞计数程序使用ImageJ插件

时空映射和粒子分析技术在细胞内 ca2 +原位信令定量中的应用

细菌群的延时成像与集体压力反应

使用双标记 （MADM） 的马赛克分析开发脑皮质的血统跟踪和克隆分析

ReAsH / FLASH标签和图像分析Tetracysteine传感器蛋白在细胞中

同时布莱特菲尔德，荧光，和光学相干断层成像收缩心脏特拉贝库莱 Ex Vivo

时空映射和粒子分析技术在细胞内 ca^{2 +}原位信令定量中的应用

使用双标记（MADM）的马赛克分析开发脑皮质的血统跟踪和克隆分析