Name: outer-boundary assisted segmentation and quantification of trabecular bones by an imagej plugin
Uploaded: 2018-03-14T14:00:00
Description: Watch this Scientific Journal Video about Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin at JoVE.com

这项工作得到了赠款 NFSC 81170806 的部分支持。作者感谢武汉大学口腔医学院的微 CT 核心设施, 帮助对大鼠股骨进行扫描和分析。

涉及动物主题的程序是按照《动物保育和使用指南》 (NIH 出版, 第八版, 2011) 进行的, 并已由武汉机构动物保育和使用委员会审查和批准。大学.
1. 软件安装
<ol><li>安装 ImageJ 软件。从 https://imagej.nih.gov/ij/下载与64位 Java 捆绑在一起的 ImageJ (版本 1.51p) 软件的 Windows 版本。将下载的软件解压到一个文件夹中, 随后将其称为 "ImageJ 目录"。 注: 小梁分析插件需要64位 java 运行时间 (?...

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本研究介绍了一种用于分析小梁骨的 ImageJ 插件, 它具有自动、高效和人性化的功效。该插件还可用于量化任何2D 或3D 对象, 用于逐层度量区域、卷和厚度。目前, 通过标准的显微 CT 分析, 每个样品的每一个小梁参数只有一个测量值, 不能完全代表所选分析区域中测量实体的特征。所述插件报告每个样本的每一个参数的逐层数量, 在选定的分析区域充分保留测量参数的分布信息, 因此更先进和敏感的?...

小梁骨显微 CT 分析是跟踪不同骨丢失情况下动物骨骼形态学变化的标准方法1,2,3, 其中几个变量与报告了骨骼的结构4。但是, 此类参数在长骨骼的骺中不均匀分布5, 并且仅报告每个样本的每个结构变量的汇总值或平均值 (由当前商用微 CT 机6,7, 但单个值不能完全表示分析区域中测量参数的特征。一层一层定量的小梁骨不仅保留了对每个变量的更多信息, 而且还能够在分析区域中对此类变量的分布进行分析, 便于随后对结构进行统计分析。在不同条件下的更改5。因此, 该方法的目的是量化微梁骨的显微 ct 扫描在每个切片水平, 这是没有在任何商业可用的微 ct 分析包目前。
为了有效地分割小梁骨切片, 需要自动分割方法。然而, 目前的显微 CT 分析标准技术是基于人工交互式轮廓, 然后是半自动插补, 将小梁骨从皮质隔间分离出来, 这是劳动密集型、易出错和与大量运算符偏差关联8,9,10。自动分割方法11,12报告, 但这种方法只有在良好的分离小梁骨和皮质骨的区域, 但不是在没有明确的分离区域。另外, 不同的样本12需要不同的分割参数, 通过尝试各种参数组合12, 手动选择适用于骨骼样本组的满意的分割参数是很繁琐的,即使在设置所有相关参数时, 分割过程也是自动的。由于骨外边界与扫描背景有最大的对比, 长骨骼的骺皮质壳在所选择的分析区域中表现出很少的变化, 根据长骨骼外边界轮廓分割方法可以可靠准确地将小梁骨从皮质壳中分离出来。这种分割方法的优点是, 分割是基于背景和骨骼的外边界之间的差异, 而不是小梁和皮质骨骼之间的差异6,12, 13, 因此通常很容易找到一个组合的分割参数, 这是令人满意的一组骨样本, 有助于更可靠地分析不同组之间的小梁变化。
在每个切片级别上, 报告了2D 分析的面积、周长和二维 (2D) 厚度, 而在 3D quantifications 中报告了体积、表面和三维 (3D) 厚度。目前的图像分析工具通常不报告此类信息, 表明所报告的程序可应用于需要此类信息的一般图像。

<table border="0" cellpadding="0" cellspacing="0" style="width:595px;" width="595">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">ImageJ</td>
			<td style="width:93px;">NIH</td>
			<td style="width:119px;">imagej</td>
			<td style="width:167px;">Any version with a java 1.8 run time</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">trabecular analysis plugin</td>
			<td style="width:93px;">Bomomics</td>
			<td style="width:119px;">bomomics</td>
			<td>free or commercial version</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Micro CT scanner</td>
			<td style="width:93px;">Scanco</td>
			<td style="width:119px;">&#956;-50</td>
			<td>micro CT from any vendor</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Computer System</td>
			<td style="width:93px;">Lenovo</td>
			<td style="width:119px;"></td>
			<td>any brand</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Windows Operating System</td>
			<td style="width:93px;">Microsoft</td>
			<td style="width:119px;">Windows 7 x64</td>
			<td>any 64-bit Windows operating system&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Office Software</td>
			<td style="width:93px;">Microsoft</td>
			<td style="width:119px;">Office 2010</td>
			<td>any speadsheet software that has xy chart function</td>
		</tr>
	</tbody>
</table>

outer-boundary assisted segmentation and quantification of trabecular bones by an imagej plugin

微计算机断层扫描 (显微 CT) 通常用于评估不同骨质流失情况下小动物骨量和微梁的显微结构特征。然而, 显微 CT 图像小梁分析的标准方法是切片半自动手工轮廓, 这是劳动密集型和易出错的。本文描述的是根据骨的外边界自动分割小梁骨的有效方法, 在适当的情况下, 在合适的情况下, 可自动识别和分割短梁骨。设置了分割参数。为了分析满意的分割参数, 给出了分割结果的图像栈, 将分割参数的所有可能组合按顺序变化, 并通过相关参数的分割结果可以易于目视检查。作为插件的质量控制特性, 模拟标准对象被量化, 在测量量可以与理论值进行比较。该插件报告了小梁性质和小梁厚度的逐层量化, 并能很容易地对所选区域内的这种性质分布进行分析。虽然逐层量化保留了关于小梁骨的更多信息, 并有助于进一步统计分析结构变化, 但此类措施无法从当前商业软件的输出中获得, 只有单一每个示例都报告每个参数的量化值。因此, 所描述的工作流是比较准确、高效地分析小梁骨的较好方法。

小梁分析插件旨在自动分割和量化小梁骨的准确性。最初, 骨外边界被发现和划定后, 一个孔充填手术, 其中任何孔内的骨外皮质壳填补。然后进行侵蚀手术, 排除外皮质骨, 并获得分割小梁骨。最后, 对分段区小梁骨的测量方法进行量化。
由于微 CT 图像固有的噪音, 分割使用预定义的任意参数往往无法准确识别骨骼的外部边界?...

Watch this Scientific Journal Video about Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin at JoVE.com

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

我们提出了一个工作流, 以分割和量化的小梁骨2D 和3D 图像基于骨骼的外部边界使用一个 ImageJ 插件。这种方法比当前手工轮廓方法更有效和准确, 并提供了一层层的 quantifications, 在当前的商业软件中是不可用的。

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 ...

The overall goal of this procedure is to quantify structural measurements of trabecular bones automatically with accuracy and efficiency. This method can help answer key questions in the image analysis field, such as how to measure irregular structures accurately with efficiency. The main advantage of this technique is that structural measurements of two-dimensional or three-dimensional objects by such a technique are more accurate and efficient than the current available quantification approaches.To begin this procedure, first install the ImageJ software and trabecular analysis plugins, as outlined in the text protocol. Open the ImageJ software. Under Plugins, BoMomics, Simulate Objects, click the Circle button.In the resulting popup window, enter 200 as the diameter, and then click OK to generate a simulated circle with a diameter of 200 pixels. Save the generated circle in TIFF format. Next, in Plugins, BoMomics, Simulate Objects, click the Square button.In the popup, enter 200 and the side length, and click OK to generate a simulated square with a side length of 200 pixels. Save it in TIFF format. Then, in the same menu, click the Sphere button.Enter 30 as the diameter, and click OK to generate the simulated sphere. Click the Plugins, 3D, Volume Viewer to view the sphere, and save it in TIFF format. Finally, in Plugins, BoMomics, Simulate Objects, click the Cylinder button.Enter 30 as the diameter and 100 as the height, and then click OK to generate the simulated cylinder. After this, click Plugins, 3D, Volume Viewer to view the cylinder, and save it in TIFF format. First, open the ImageJ software, and open or import a scanned image.Slide the bottom scroll bar to choose a slice, and then click the Image, Adjust, Threshold button. In the Threshold popup window, adjust the minimum and maximum threshold values to ensure that the bones are well separated from the background. Record the minimal threshold value as the cortical bone threshold value.Next, click the Plugins, BoMomics, Trabecular Parameter Profiling button. In the popup window, set the Slice Index to the position of the representative slice. Set the Cortical Bone, Range, and Step values to calculate a set of cortical thresholds for profiling segmentation parameters.After this, set the Noise Diameter, Step, and Range values to specify a set of noise values for the analysis. Set the Hole Diameter, Step, and Range values for calculating a set of hole values. Click OK to perform the parameter profiling.In the Parameter Profiling Results window, visually check the segmentation results, and select a slice layer where the bone's outer boundary is outlined accurately. Then, retrieve the profiling parameters from the corresponding entry in the Parameter Profiling Results table. To begin analyzing the trabecular bones, open the ImageJ software and open or import a scanned image.Click the Plugins, BoMomics, Trabecular Segmentation button. Fill in appropriate analysis parameters, as shown here. Next, click OK to perform the trabecular segmentation.Visually inspect the results in the Trabecular Segmentation Results window. Then, save the extracted trabecular bones shown in the Segmented Trabecular Bones window in TIFF format for further analysis. After this, click the Plugins, BoMomics, Trabecular Analysis button, and fill in the appropriate analysis parameters, as outlined in the text protocol.In the Results Reporting section, select one or more parameters to be measured where the options are trabecular bone volume, total volume, and thickness measured either two-dimensionally or three-dimensionally. To perform trabecular analysis, select the checkboxes for both 2D and 3D, and then click OK.To begin quantifying objects, open a simulated image in the ImageJ software. Select the Plugins, BoMomics, Trabecular Analysis button, and fill in the appropriate analysis parameters, keeping the default values for Start, End, Outline Boundary, and Trabecular Bones, while setting Noise Reduction Diameter, Hole Filling Diameter, and Cortical Thickness Diameter to zero.In the Results Reporting section, select both 2D and 3D as the parameters to be measured. Then, click OK to perform trabecular analysis on the simulated object. After this, calculate the calibrated bone volume, total volume, bone mineral content, bone volume fraction, and bone mineral density in spreadsheet columns, and analyze the data, as outlined in the text protocol.In this study, an ImageJ plugin is used to automatically segment and quantify trabecular bones. Representative parameter profiling analysis using different parameter conditions reveals that some combinations are more accurate when delineating a bone's outer boundaries than others. Next, segmentation and analysis is performed to quantify measurements of the trabecular bones.The results of this segmentation can be visually checked slice-by-slice. The raw quantifications of the bone volume, the total volume, the sum of gray values, and the thickness, either in two or three dimensions, can be reported depending on which options are selected during analysis. The calibration information is extracted from the scanned micro-CT dataset, and calibrated measurements of bone volume, total volume, bone mineral content, bone volume fraction, and bone mineral density are then calculated.Their distributions can then be profiled in the selected analyzing region, layer-by-layer, against the layer positions. Once mastered, this technique can quantify trabecular bones of 500 image layers in 10 to 20 minutes if it's performed properly. We first had the idea for this method when we found that the results reported by the micro-CT vendor software were not reproducible when the same dataset was analyzed by the same experienced operator.After watching this video, you should have a good understanding of how to choose appropriate bone segmentation parameters and perform analysis of long bones with minimal user interactions.

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