Lung Image Database with Pathologic Correlates

描述：（申请人提供） 本申请是应一项特别要求而提出， 代表肺癌基本事实的广义CT衍生数据库， 不是假设驱动的。我们的总体目标是帮助建立一个 数据库，并通过这一努力协助有条不紊地发展 适当的肺癌筛查工具和方案。我们的团队， 在国家合作项目方面具有公认的经验， 将为联合体提供： 一组特征明确的肺癌研究受试者， 常见的肺癌模拟，如组织胞浆菌病，由优秀的支持 放射科医生和病理学家。 在CT成像协议的发展专业知识。 一个功能性电子传输系统，用于从多个站点传输CT数据集， 这些数据集的分析和存档，DICOM标准的专业知识， 发布网络报告。 CT数据点的时间匹配方法，在纵向 随访患者，匹配切除的膨胀叶数据， 将组织病理学数据与原始患者CT进行比较。 计算形态学的专业知识（即数学描述） 复杂结构、其可视化以及其衍生的CT图像）。我们 我打算将其应用于切除的肺肿瘤的子集，以帮助定义 病理和CT基本事实。 图像重建算法。这对我们的未来至关重要。 确定和实施CT方法中需要的改进， 最大限度地提高肺内微小早期病变的检出率 软组织和气道。 数据来自两个不同的CT制造商的多层螺旋CT扫描仪。 通过数学推导的虚拟肺部模型，包括早期肺癌， 开发，用于设计扫描和重建方法。

DESCRIPTION: (Provided by Applicant) This application is in response to a specific request to establish a generalized CT-derived database representing ground truth in lung cancer and is not hypothesis-driven. Our broad goal is to help in the building of this database, and through that effort assist with the methodical development of appropriate lung cancer screening tools and protocols. Our group, with recognized experience in cooperative national projects, and with a broad perspective, will provide for the consortium : a well characterized group of study subjects with lung cancer, and with common lung cancer mimics such as histoplasmosis, supported by excellent radiologists and pathologists. expertise in the development of CT imaging protocols. a functional electronic transfer system for CT data sets from multiple sites, analysis and archiving of such data sets, expertise in DICOM standards, and in the issuing of web-based reports. methods for temporal matching of CT data points, important in the longitudinal follow-up of patients, and in matching excised inflated lobe data and histopathological data to the original patient CT. expertise in computational morphology, (i.e. the mathematical description of complex structures, their visualization, and their derived CT images). We intend to apply this to a subset of resected lung tumors to help define pathological and CT ground truth. Image reconstruction algorithms. This is critically important for the identification and implementation of needed improvements in CT methods to maximize the chance of detection of subtle early lesions within the lung parenchyma and airways. data from two different CT manufacturers multi-slice helical CT scanners. with mathematically derived virtual lung models, including early lung cancer development, for use in design of scanning and reconstruction methods.