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: 7538227
• 负责人: Susan Ng
• 金额: $ 34.01万
• 依托单位: REAL-TIME TOMOGRAPHY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-05-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7538227
• 关键词: Address; Algorithms; Anatomy; Anisotropy; Appearance; Applications Grants; Attenuated; Back; Biopsy; Breast; Clinical; Computer Systems Development; Computer software; Data; Data Set; Diagnosis; Diagnostic; Diagnostic Imaging; Digital Mammography; Ensure; Frequencies; Future; Goals; Grant; Image; Image Guided Biopsy; Imaging Phantoms; Intellectual Property; Letters; Licensing; Light; Location; Malignant Neoplasms; Mammaplasty; Mammography; Manufacturer Name; Marketing; Masks; Medical; Methods; Modality; Morphologic artifacts; Normal tissue morphology; Numbers; Pennsylvania; Phase; Physicians; Pliability; Plug-in; Positioning Attribute; Procedures; Process; Public Health; Purpose; Range; Rate; Reader; Research; Resolution; Running; Screening procedure; Shadowing (Histology); Simulate; Slice; Solutions; Speed; Surgeon; Surgical Clips; System; Techniques; Technology; Thick; Time; Today; Universities; Vendor; base; calcification; commercialization; digital; experience; image reconstruction; improved; innovation; interest; malignant breast neoplasm; programs; rapid technique; reconstruction; response; size; tomography

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 eight 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 II proposal, we seek to refine our existing DBT reconstruction algorithm and filters to enhance the different clinical indications of breast cancer that is crucial for proper diagnosis. Our ultimate goal is to achieve a reconstruction rate of at least 20 frames per second (fps). In Phase II, we propose the following specific aims: (1) Refine our backprojection operators on a GPU using general-purpose GPU programming techniques. (2) Refine our imaging filtering methods to specifically enhance images of calcifications and masses using general-purpose GPU programming techniques. (3) Develop thick-slice rendering methods and implement them on a GPU. (4) Explore methods for handling large data sets on the GPU. The University of Pennsylvania will provide assessments of image quality of the image reconstructions and will provide simulated phantom images to allow optimization of the image backprojection and filtering methods. PUBLIC HEALTH RELEVANCE: 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.

描述（申请人提供）：根据初步临床结果，人们普遍认为数字乳腺断层合成（DBT）有潜力在未来取代乳房X光检查。目前至少有八家公司正在开发 DBT 成像系统，其中三家公司很少或根本没有开发初级审查工作站的经验。实时断层扫描（RTT）拥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，用于数字乳腺断层合成图像的初步诊断。我们认为，基于DBT数据集的庞大、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，专用工作站是必要的。为了满足高吞吐量的需求，我们特别建议开发和实现一种重建算法，该算法将允许在基于 PC 的专用高端图形处理器单元 (GPU) 上通过乳房体积对任意平面进行动态实时重建和渲染 (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且优先。支持减少灾害风险的理由有很多。首先，现有的 GPU 硬件几乎可以实现断层扫描图像的即时反投影和滤波 (BPF) 重建；该硬件基本上是现成的并且随时可用。其次，目前正在生成的乳房断层合成数据集是各向异性的，面内分辨率约为 0.07-0.1 mm2，面外分辨率为 1 mm。这种各向异性是由所得图像集的大小以及生成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 将允许任意重建，而不会对存储或速度产生不利影响。 RTT的长期目标是开发一个基于DRR原则的初审工作站。在这个 II 期提案中，我们寻求完善现有的 DBT 重建算法和过滤器，以增强乳腺癌的不同临床适应症，这对于正确诊断至关重要。我们的最终目标是实现至少 20 帧每秒 (fps) 的重建速率。在第二阶段，我们提出以下具体目标：（1）使用通用 GPU 编程技术在 GPU 上改进我们的反投影算子。 (2) 改进我们的成像过滤方法，使用通用 GPU 编程技术专门增强钙化和肿块的图像。 (3)开发厚片渲染方法并在GPU上实现。 (4)探索在GPU上处理大数据集的方法。宾夕法尼亚大学将提供图像重建的图像质量评估，并将提供模拟幻影图像，以优化图像反投影和过滤方法。公共健康相关性：由于 2D 图像是由 3D 乳房解剖结构构成的，因此乳房 X 光检查（包括数字乳房 X 光检查）受到许多基本限制。由于正常组织的叠加，乳房 X 光检查可能会产生假阳性结果，并且由于正常组织隐藏或掩盖了癌症，因此乳房 X 光检查可能会漏掉癌症。数字乳腺断层合成（DBT）是一种断层摄影成像方法，有可能解决上述两个乳腺X线摄影问题。多家制造商正在开发断层合成成像系统。然而，正如临床数字乳房X线摄影系统的持续部署所表明的那样，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。我们建议开发一个用于 DBT 的初级医师审查工作站。这是任何临床 DBT 系统的重要组成部分。