Development of a Volume Imaging X-Ray Micro-CT Scanner

9317816里特曼这项建议的目标是制造和评估一台用于生物标本的体积成像X光微型CT扫描仪原型(通过新的断层图像重建、3D图像分析和显示软件进行增强)。扫描仪的设计灵感来自埃克森美孚公司一个研究小组为地质目的开发的独特的微型CT扫描仪。埃克森美孚研究团队的成员将为复制其扫描仪的重要方面提供必要的咨询。这一新的能力具有巨大的潜力，可以提供对细胞水平的机制如何整合在微观和宏观尺度的器官解剖中表达自己的定量见解。这台拟议的扫描仪将生成至少5123立方体素(每面10到40米)的体积图像。这种扫描仪通过在合理的时间内以更高的空间分辨率成像更大的体积，扩展了目前主要为材料科学和无损测试目的开发的微型CT方法。这是对光学显微镜和传统X射线放大技术的改进，大大提高了图像数据分析的后勤保障。之所以采用计算机断层成像方法(不需要一次重组扫描的切片)，也是因为我们已经开发了用于定量分析和显示3D体积图像的软件。该软件可以容易地扩展以处理将由所提议的扫描仪生成的巨大3D图像(例如，高达109个体素)。我们近年来为3D全身扫描CT图像数据开发的几种软件方法应该会极大地扩展X射线Micro-CT方法的能力，如下所示：a)扫描大于荧光屏大小的对象的能力，因为我们可以使用我们的合作者俄勒冈州立大学的Faridani博士和Smith博士开发的“局部”(与传统的“全局”相比)重建算法。这个算法只需要在较大的样本中通过感兴趣的体积来“看到”投影。因此，可以扫描小动物完整身体内的器官，而不需要扫描整个身体的横向解剖范围，从而大大降低了扫描仪的成本。B)Faridani博士开发了另一种新算法，该算法可以提供几乎两倍于传统的视角数与沿横向X射线吸收剖面的样品数之间的关系所“允许”的空间分辨率。C)使用宾夕法尼亚州立大学希金斯博士开发的算法，自动分割大型而复杂的3D图像，例如整个动脉树及其数千个分支。D)使用我们实验室开发的用于分析大血管动脉树几何形状的算法和图像分析软件的修改版本，能够自动分析分段的血管树的节段尺寸和分支角度。

9317816 Ritman The objective of this proposal is to fabricate and evaluate a prototype volume imaging x-ray micro-CT scanner (augmented by novel tomographic image reconstruction, 3D image analysis and display software) for application to biological specimens. The scanner design is inspired by a unique micro- CT scanner developed by a research group of the Exxon company for their geological purposes. Members of the Exxon Research team will provide consultations needed for duplication of important aspects of their scanner. This new capability has great potential for providing quantative insights into how mechanisms at the cellular level integrate to express themselves in the anatomy of organs at the micro and macroscopic scale. This proposed scanner will generate volume images of at least 5123 cubic voxels (10 to 40m on a side). This scanner extends current micro-CT methods, developed primarily for material sciences and nondestructive testing purposes, by imaging larger volumes with greater spatial resolution, within a reasonable period of time. This is an improvement over optical microscopic and conventional x-ray magnification techniques in that the logistics of image data analysis are greatly improved. The reason a computed tomographic imaging approach (which eliminates re-assembly of one-at-the-time scanned slices) and because we have already developed software for quantitative analysis and display of the 3D volume images. This software can be readily expanded to handle the huge 3D images (e.g., up to 109 voxels) to be generated with the proposed scanner. Several software approaches, which we have developed in recent years for 3D whole body scanning CT image data, should greatly extend the power of the x-ray micro-CT methodology as follows: a) Ability to scan objects greater than the size of the fluorescent screen because we can use the 'local' (as compared to the conventional 'global') reconstruction algorithm that our collaborators Drs. Faridani and Smith of Oregon State University have developed. This algorithm needs to 'see' only the projection through the volume of interest within a larger specimen. Consequently organs within the intact body of small animals can be scanned without the need to scan the entire transverse anatomic extent of the body, thereby greatly reducing scanner cost. b) Another new algorithm has been developed by Dr. Faridani that may provide almost double the spatial resolution "allowed" by the traditional relationship between numbers of angles-of-view and numbers of samples along the transverse x-ray absorption profile. c) Ability to automatically segment large and complex 3D images such as the entire arterial trees with its thousands of branches, using an algorithm of the type developed by Dr. Higgins of Pennsylvania State University. d) Ability to automatically analyze the segmented vascular trees for segmental dimensions and branching angles using modified versions of the algorithms and image analysis software developed in our laboratory for analysis of macrovascular arterial tree geometry.