Standard Database for CT Lung Images

CT 肺部图像标准数据库

• 批准号: 6933050
• 负责人: Samuel G. Armato
• 金额: $ 35.73万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-08-20 至 2007-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6933050
• 关键词: bioimaging /biomedical imaging; cancer information system; clinical research; computed axial tomography; computer system design /evaluation; cooperative study; human subject; image processing; lung neoplasms

The broad, long-term objective of this research proposal is to create a publicly available standard database of spiral computed tomography (CT) lung images. This lung image database will become an essential resource for the development of computer-aided diagnostic (CAD) techniques designed to help radiologists identify lung cancer in CT scans. The need for a standard lung image database is based on two recent developments. The first is the advancement of multi-slice CT scanners, which acquire images of multiple anatomic sections during each gantry rotation. Consequently, these scanners may generate an extensive amount of image data. The second development is the growing awareness among the American public and clinicians of the potential benefits of lung cancer screening using a low-dose spiral CT protocol. These developments are expected to dramatically increase the burden on radiologists. Moreover, primary interpretation from softcopy display will become a practical necessity. What emerges from this scenario is a requirement for automated image processing methods that provide radiologists with quantitative information about suspicious abnormalities in the CT image data. Radiologists will then incorporate this information into their diagnostic decision-making process, with the expectation that cancer-detection sensitivity may be improved while decreasing both observer variability and interpretation time. Creation of a standard lung image database is critical to the endeavor of imaging research. This proposal addresses the important clinical and technical issues relevant to the creation of such a database. The specific aims of the proposed research are: (1) to identify the clinical requirements that must be imposed on a standard CT lung image database, (2) to address the technical issues and criteria involved with case selection for the CT lung image database, (3) to collect cases for the CT lung image database as a member of the Lung Image Database Consortium, (4) to develop strategies for the assessment of image processing and CAD methods using the CT lung image database, and (5) to investigate the effect of image reconstruction, multi-modality image registration, and registration of images acquired at different times on the utility of the CT lung image database. As a member of the Consortium, we would demonstrate the flexibility necessary to reach consensus on the creation of a database that will serve as a standard resource for imaging research. The ideas resented in this proposal are expected to stimulate the efforts of the Consortium toward that goal.

该研究计划的广泛、长期目标是创建一个公开可用的螺旋计算机断层扫描 (CT) 肺部图像标准数据库。该肺部图像数据库将成为计算机辅助诊断 (CAD) 技术开发的重要资源，旨在帮助放射科医生在 CT 扫描中识别肺癌。对标准肺部图像数据库的需求基于最近的两项发展。首先是多层 CT 扫描仪的进步，它在每次机架旋转期间获取多个解剖切片的图像。因此，这些扫描仪可以生成大量的图像数据。第二个进展是美国公众和临床医生越来越意识到使用低剂量螺旋 CT 方案进行肺癌筛查的潜在益处。预计这些发展将大大增加放射科医生的负担。此外，来自软拷贝显示的初步解释将成为实际需要。这种情况需要自动化图像处理方法，为放射科医生提供有关 CT 图像数据中可疑异常的定量信息。然后，放射科医生会将这些信息纳入他们的诊断决策过程中，期望可以提高癌症检测的灵敏度，同时减少观察者的变异性和解释时间。创建标准的肺部图像数据库对于影像研究的努力至关重要。该提案解决了与创建此类数据库相关的重要临床和技术问题。拟议研究的具体目标是：(1) 确定对标准 CT 肺部图像数据库必须提出的临床要求，(2) 解决 CT 肺部图像数据库病例选择所涉及的技术问题和标准， (3) 作为肺部图像数据库联盟的成员收集 CT 肺部图像数据库的病例，(4) 制定使用 CT 肺部图像数据库评估图像处理和 CAD 方法的策略，以及 (5) 进行调查图像重建、多模态图像配准的效果，利用 CT 肺部图像数据库对不同时间获取的图像进行配准。作为联盟的成员，我们将展示在创建数据库方面达成共识所需的灵活性，该数据库将作为成像研究的标准资源。该提案中所反对的想法预计将刺激联盟为实现这一目标而付出的努力。