Lung Image Database with Pathologic Correlates

描述：(申请人提供) 此应用程序是为了响应特定请求而建立 代表肺癌和肺癌基本事实的通用CT衍生数据库 并不是由假设驱动的。我们的广泛目标是帮助建立这个 数据库，并通过这一努力帮助有条不紊地开发 适当的肺癌筛查工具和方案。我们的团队，有 在国家合作项目方面有公认的经验，并具有广泛的 从长远来看，将为财团提供： 一组特征明确的肺癌研究对象，并与 常见的肺癌模拟组织胞浆菌病，由卓越支持 放射科医生和病理学家。 在CT成像方案开发方面的专业知识。 一种用于来自多个站点的CT数据集的功能电子传输系统， 此类数据集的分析和归档、DICOM标准方面的专业知识以及 发布基于网络的报告。 CT数据点的时间匹配方法，在纵向上很重要 对患者的随访，并在匹配切除的肺叶膨胀数据和 将组织病理学数据转换为原始患者的CT。 计算形态学方面的专业知识(即数学描述 复杂结构、其可视化及其衍生的CT图像)。我们 打算将这一方法应用于切除的肺肿瘤的子集，以帮助确定 病理和CT基本事实。 图像重建算法。这对于 确定和实施CT方法中需要改进的部分，以 最大限度地增加发现肺内微小早期病变的机会 实质和呼吸道。 来自两家不同CT制造商的多层螺旋CT扫描仪的数据。 利用数学推导的虚拟肺模型，包括早期肺癌 开发，用于扫描和重建方法的设计。

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.