Visualization of Multi-Resolution Reconstructions Using Interactive Stereoscopy

使用交互式立体视觉进行多分辨率重建的可视化

• 批准号: 7313679
• 负责人: ARKADIUSZ SITEK
• 金额: $ 20.19万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-10 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7313679
• 关键词: Algorithms; Clinic; Clinical; Clinical Data; Clip; Computer Graphics; Computer Simulation; Computer software; Computers; Data; Depth; Detection; Development; Devices; Discipline of Nuclear Medicine; Early Diagnosis; Feedback; Goals; Human; Image; Image Analysis; Imagery; Lead; Lesion; Lighting; Location; Medical Imaging; Methods; Modeling; Motivation; Numbers; Optics; Patient Care; Performance; Physicians; Positioning Attribute; Positron-Emission Tomography; Qualitative Evaluations; Receiver Operating Characteristics; Recovery; Resolution; Retinal Cone; Scanning; Screening for cancer; Sensitivity and Specificity; Slice; Standards of Weights and Measures; Techniques; Technology; Three-Dimensional Image; Three-Dimensional Imaging; Validation; Work; attenuation; base; clinical Diagnosis; design; image reconstruction; image visualization; improved; multidisciplinary; novel; reconstruction; size; stereoscopic; tomography; tool

DESCRIPTION (provided by applicant): Historically, nuclear medicine imaging has been done using 2D views. With the advent of computers and tomography, 3D images were acquired and stored in regular arrays of voxels. Although a logical extension from 2D, representation of a 3D object as a stack of 2D images may not be optimal for lesion detection. This is because voxels with rectangular geometry do not accurately approximate the geometry of the imaged objects. This mismatch is especially significant for nuclear medicine studies where degrading physical factors force the images to be reconstructed on grids that consist of large cubic voxels. Considering that the lesions are small and may be comparable in size to voxels, the inadequacy of cubic voxel approach becomes evident. Our hypothesis is that by using the multi-resolution image representation proposed in this work, the images can be reconstructed and presented more accurately and efficiently than using the regular grids, thus resulting in lesion detection improvement using FDG-PET. We chose to represent the image as a set of points in space (point cloud) with unrestricted locations and intensities assigned to each point (node) with volume represented by a set of non-overlapping tetrahedrons defined by the nodes. The selection of this representation was dictated by two factors. First, each image will have its own grid that will be designed to accurately and efficiently represent each image. By using unrestricted node positions, a geometry with arbitrary local resolution that varies across the image volume can be modeled. Second, the tetrahedral geometry of the image will take advantage of recent revolutionary progress in computer graphics hardware in order to use advanced visualization techniques for stereoscopic interactive 3D visualization of the imaging data. The work proposed here will create a framework for voxel-less multi- resolution representation of the image in nuclear medicine. It includes multidisciplinary development of the tomographic reconstruction and stereoscopic visualization methods using medical imaging and computer graphics. The work involves design and creation of software for reconstruction and stereoscopic display of tetrahedron based images and evaluation against human observers for the lesion detection task. Early detection of cancer tremendously improves the chances of recovery. This proposal directly benefits patient care by providing tools that will lead to early detection of small lesions that are undetectable using current technology.

描述（由申请人提供）：历史上，核医学成像是使用 2D 视图完成的。随着计算机和断层扫描的出现，3D 图像被采集并存储在规则的体素阵列中。尽管是 2D 的逻辑扩展，但将 3D 对象表示为一堆 2D 图像可能不是病变检测的最佳选择。这是因为具有矩形几何形状的体素不能准确地近似成像对象的几何形状。这种不匹配对于核医学研究尤其重要，其中退化的物理因素迫使图像在由大立方体素组成的网格上重建。考虑到病变很小并且大小可能与体素相当，立方体素方法的不足变得显而易见。我们的假设是，通过使用本工作中提出的多分辨率图像表示，可以比使用规则网格更准确、更有效地重建和呈现图像，从而改进 FDG-PET 的病变检测。我们选择将图像表示为空间中的一组点（点云），每个点（节点）的位置和强度不受限制，其体积由节点定义的一组不重叠的四面体表示。该代表的选择由两个因素决定。首先，每个图像都有自己的网格，该网格旨在准确有效地表示每个图像。通过使用不受限制的节点位置，可以对具有随图像体积变化的任意局部分辨率的几何体进行建模。其次，图像的四面体几何形状将利用计算机图形硬件的最新革命性进展，以便使用先进的可视化技术来实现成像数据的立体交互式 3D 可视化。这里提出的工作将为核医学图像的无体素多分辨率表示创建一个框架。它包括使用医学成像和计算机图形学的断层扫描重建和立体可视化方法的多学科发展。这项工作涉及设计和创建用于重建和立体显示基于四面体的图像的软件，以及针对人类观察者对病变检测任务的评估。癌症的早期发现极大地提高了康复的机会。该提案通过提供能够早期发现使用当前技术无法检测到的小病变的工具，直接有利于患者护理。