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Dynamic real-time reconstruction and rendering of breast tomosynthesis images

Dynamic real-time reconstruction and rendering of breast tomosynthesis images
乳腺断层合成图像的动态实时重建与渲染
批准号:
7221319
负责人:
Susan Ng
金额:
$10.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-05-01 至 2008-10-31

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项目成果

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中文摘要
翻译
描述(由申请人提供):基于初步的临床结果,人们普遍认为数字乳腺断层合成(DBT)在未来有可能取代乳房x线摄影。目前至少有五家公司正在开发DBT成像系统,其中三家公司很少或没有开发主要审查工作站的经验。实时断层扫描(RTT)具有开发医疗工作站的经验。RTT目前正在开发一个医生审查工作站,用于数字乳房断层合成图像的初步诊断。鉴于DBT数据集的庞大规模、乳腺成像对图像质量的严格要求,以及乳腺筛查和诊断对高通量的需求,我们认为有必要建立一个专用工作站。为了满足高吞吐量的需求,我们特别提出开发和实现一种重建算法,该算法将允许在专用的高端pc图形处理器单元(GPU)上通过乳房体积动态实时重建和渲染任意平面(DRR)。我们相信GPU技术的进步使得按需重建断层合成图像成为可能和优先。支持dr的理由有很多。首先,目前存在的GPU硬件允许几乎即时的反投影和滤波(BPF)重建断层图像;这种硬件基本上是现成的,随时可用。其次,目前生产的乳腺断层合成数据集具有各向异性,面内分辨率约为0.07-0.1 mm2,面外分辨率为1 mm。这种各向异性是由最终图像集的大小和产生这些数据所需的时间所必需的。然而,在DBT中,可以在任何位置重建图像;DRR允许任意重建,而不会对存储或速度产生不利影响。RTT的长期目标是建立一个基于DRR原则的初级审查工作站。在这个第一阶段的提案中,我们寻求实现和优化我们现有的DBT重建算法来证明可行性。我们的最终目标是实现至少每秒5帧(fps)的重建率。在第一阶段,我们提出以下具体目标:(1)使用通用GPU编程技术在GPU上实现和优化BPF。(2)实现一个具有简单图形用户界面的查看器来渲染重建图像。(3)通过比较gpu重建图像与我们目前基于cpu的算法生成的图像,评估渲染图像的图像质量,使用宾夕法尼亚大学的临床和幻影图像作为测试数据。如果能够实现持续的重建和2帧/秒的渲染速率,则认为第一期项目成功。在第二阶段,我们将继续开发工作站,特别是研究提高帧率、减少用户交互和获得最大可能吞吐量的方法。乳房x光检查(包括数字乳房x光检查)受到一些基本的限制,因为二维图像是由三维乳房解剖构成的。由于正常组织的叠加,乳房x光检查可能产生假阳性结果,而由于正常组织隐藏或掩盖了癌症,乳房x光检查可能会遗漏癌症。数字乳腺断层合成(DBT)是一种断层成像方法,有可能解决乳房x线摄影的上述两个问题。多家制造商正在开发断层合成成像系统。然而,正如正在进行的临床数字乳房x光检查系统所表明的那样,采集技术的开发只是使DBT成为临床现实所需努力的一小部分。我们建议建立一个DBT的主治医师评审工作站。这是任何临床DBT系统的重要组成部分。
英文摘要
DESCRIPTION (provided by applicant): It is widely believed that digital breast tomosynthesis (DBT) has the potential to replace mammography in the future, based on preliminary clinical results. At least five companies are currently developing DBT imaging systems, three of whom have little or no experience developing primary review workstations. Real-Time Tomography (RTT) has the experience to develop medical workstations. RTT is currently in the process of developing a physician review workstation for the primary diagnosis of digital breast tomosynthesis images. We believe that a dedicated workstation is necessary based upon the large size of DBT datasets, the stringent image quality requirements for breast imaging, and the need for high-throughput in both breast screening and diagnosis. To address the need for high-throughput, we specifically propose to develop and implement a reconstruction algorithm that will allow dynamic real-time reconstruction and rendering (DRR) of arbitrary planes through the breast volume on a dedicated high-end PC-based graphics processor unit (GPU). We believe that the advances in GPU technology make it both possible and preferential to reconstruct tomosynthesis images on demand. There are many reasons to favor DRR. First, the GPU hardware that exists today allows nearly instantaneous back-projection and filtered (BPF) reconstruction of tomographic images; this hardware is essentially off-the- shelf and readily available. Second, breast tomosynthesis datasets currently being produced are anisotropic, having in-plane resolution of approximately 0.07-0.1 mm2 and out-of-plane resolution of 1 mm. This anisotropy is necessitated by the size of the resultant image set, and the time required to produce those data. However, in DBT it is possible to reconstruct images at any location; DRR would allow arbitrary reconstruction without adversely impacting either storage or speed. The long-term goal of RTT is to develop a primary review workstation based on the DRR principle. In this Phase I proposal, we seek to implement and optimize our existing DBT reconstruction algorithm to demonstrate feasibility. Our ultimate goal is to achieve a reconstruction rate of at least 5 frames per second (fps). In Phase I, we propose the following specific aims: (1) Implement and optimize BPF on a GPU using general-purpose GPU programming techniques. (2) Implement a viewer with a simple graphical user interface to render the reconstructed images. (3) Assess the image quality of the rendered images by comparing the GPU-reconstructed images to those produced with our current CPU-based algorithm using clinical and phantom images from the University of Pennsylvania as test data. The Phase I project will be deemed successful if a sustained reconstruction and rendering rate of 2 fps can be achieved. In Phase II, we would continue the development of the workstation, specifically working on methods to increase the frame rate, minimize user interactions and obtain the greatest possible throughput. Mammography (including digital mammography) is subject to a number of fundamental limitations because 2D images are made of the 3D breast anatomy. Mammograms can produce false positive findings due to the superposition of normal tissues, and cancers can be missed in mammograms because normal tissue hide or mask the cancer. Digital breast tomosynthesis (DBT) is a tomographic imaging method with the potential to solve both of the above problems of mammography. Tomosynthesis imaging systems are being developed by multiple manufacturers. However, as has been made clear from the ongoing deployment of clinical digital mammography systems, the development of the acquisition technology is only a small part of the effort that will be required to make DBT a clinical reality. We propose to develop a primary physician review workstation for DBT. This is an essential part of any clinical DBT system.
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Dynamic real-time reconstruction and rendering of breast tomosynthesis images
  • 批准号:
    7538227
  • 项目类别:
  • 资助金额:
    $34.01万
  • 财政年份:
    2007
  • 负责人:
    Susan Ng
  • 依托单位:
Dynamic real-time reconstruction and rendering of breast tomosynthesis images
  • 批准号:
    7655338
  • 项目类别:
  • 资助金额:
    $40.99万
  • 财政年份:
    2007
  • 负责人:
    Susan Ng
  • 依托单位:
海外基金