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

本提案的目的是制造和评估一种原型体积成像x射线微型ct扫描仪（通过新型断层图像重建，3D图像分析和显示软件增强），用于生物标本。扫描仪的设计灵感来自于埃克森公司的一个研究小组为他们的地质目的而开发的一种独特的微型CT扫描仪。埃克森研究小组的成员将提供必要的协商，以复制其扫描仪的重要方面。这种新能力具有很大的潜力，可以定量地了解细胞水平上的机制如何在微观和宏观尺度上整合在器官解剖中表达自己。这种提议的扫描仪将产生至少5123立方体素的体积图像（每边10到40米）。该扫描仪扩展了目前主要用于材料科学和无损检测目的的微型ct方法，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。这是对光学显微镜和传统x射线放大技术的改进，因为图像数据分析的物流得到了极大的改善。原因是计算机层析成像方法（它消除了一次扫描切片的重新组装），因为我们已经开发了用于定量分析和显示3D体图像的软件。该软件可以很容易地扩展，以处理巨大的3D图像（例如，高达109体素）产生与拟议的扫描仪。近年来，我们为3D全身扫描CT图像数据开发了几种软件方法，可以极大地扩展x射线微CT方法的功能，如下所示：a)扫描比荧光屏尺寸更大的物体的能力，因为我们可以使用“局部”（与传统的“全局”相比）重建算法。俄勒冈州立大学的法里达尼和史密斯。该算法只需要“看到”较大样本中感兴趣体积的投影。因此，可以扫描小动物完整身体内的器官，而无需扫描身体的整个横向解剖范围，从而大大降低了扫描仪的成本。b) Faridani博士开发的另一种新算法可以提供几乎两倍的空间分辨率，这是传统的视角数量和沿横向x射线吸收剖面的样品数量之间的关系所“允许”的。c)使用宾夕法尼亚州立大学希金斯博士开发的算法，自动分割大型复杂3D图像的能力，例如整个动脉树及其数千个分支。d)能够使用我们实验室开发的大血管动脉树几何分析算法和图像分析软件的修改版本，自动分析分割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.