权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Optimizing MDCT display for detection and diagnosis of pulmonary embolism

优化 MDCT 显示以检测和诊断肺栓塞

基本信息

批准号：
7755013
负责人：
WALTER F GOOD
金额：
$ 37.13万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-01-01 至 2011-12-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Multi-detector CT (MDCT) is rapidly becoming the primary imaging modality for detection and diagnosis of pulmonary embolism (PE). Its main limitations are its inability to reliably depict sub-segmental arteries and the large volume of image data that must be reviewed for each study. This application proposes to implement a stereographic display of appropriately segmented arterial trees, which can be manipulated in real time, with the intent of improving both the accuracy and efficiency of these studies. Most previous methods for segmenting pulmonary vessels are less than optimal in that, while they generally combine the eigenvectors of the Hessian matrix to derive a local scalar measure of cylindricity, in the process they lose information about the directions of the local curvatures. By exploiting all information in structure tensor fields derived from 3D datasets, and in particular by employing tensor voting methods to identify voxels comprising surfaces of vessels and bifurcations, we expect to significantly improve the segmentation process and the depiction of small arteries. A flexible mechanism will be developed for displaying various stereographic views of the segmented data in real time, at the option of the radiologist. Rendering methods, tailored specifically to viewing PE, will be developed. Multiple raycasting algorithms will be incorporated into the system because certain methods are better for detection while others are better for assessing a feature once it has been detected. Images comprised of local parameters used in segmenting vascular trees, or parameters that characterize statistical properties of vessel distributions, will be displayable at the readers' discretion. A retrospective LROC study (8 readers, 4 display modes, 100 cases) will be performed to evaluate the newly developed methods. This study will address performance and efficiency as well as certain psychophysical issues such as subjective acceptance of the display, speed of operation, pattern of gaze in 3D versus 2D, and the relative propensity of the various display modes to induce fatigue. To compensate for an imperfect gold standard for case verification, mixture distribution analysis will also be applied and compared to LROC results. This study should identify a set of images containing PEs that can be readily seen on stereo displays, but cannot be detected as easily on traditional displays, or vice versa - which should help clarify benefits of stereo for radiographic applications and provide useful information for making future refinements to the display.

描述（由申请人提供）：多层螺旋CT（MDCT）正迅速成为检测和诊断肺栓塞（PE）的主要成像模式。它的主要局限性是不能可靠地描绘亚段动脉，并且每次研究都必须审查大量的图像数据。本申请提出实现适当分割的动脉树的立体显示，其可以在真实的时间内进行操作，目的是提高这些研究的准确性和效率。大多数先前的用于分割肺血管的方法不是最佳的，因为虽然它们通常联合收割机组合Hessian矩阵的特征向量以导出圆柱度的局部标量测量，但是在该过程中它们丢失了关于局部曲率的方向的信息。通过利用来自3D数据集的结构张量场中的所有信息，特别是通过采用张量投票方法来识别包括血管和分叉表面的体素，我们期望显着改善分割过程和小动脉的描绘。将开发一种灵活的机制，用于根据放射科医生的选择，真实的实时显示分割数据的各种立体视图。渲染方法，专门为观看PE，将被开发。多个光线投射算法将被纳入系统，因为某些方法更适合检测，而其他方法更适合在检测到特征后对其进行评估。由血管树分割中使用的局部参数或表征血管分布统计特性的参数组成的图像将由阅片者自行决定是否显示。将进行一项回顾性LROC研究（8名阅片员，4种显示模式，100例病例），以评价新开发的方法。这项研究将解决性能和效率以及某些心理物理问题，如显示器的主观接受度，操作速度，3D与2D的凝视模式，以及各种显示模式引起疲劳的相对倾向。为了弥补病例验证的不完美金标准，还将应用混合分布分析并与LROC结果进行比较。本研究应确定一组包含PE的图像，这些图像在立体显示器上很容易看到，但在传统显示器上无法轻易检测到，反之亦然-这应有助于阐明立体影像学应用的益处，并为将来改进显示器提供有用的信息。