Reeves A P, Biancardi A M, Yankelevitz D, Fotin S, Keller B M, Jirapatnakul A, Lee J
Cornell University, Ithaca, NY 14853, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3715-8. doi: 10.1109/IEMBS.2009.5334807.
The Public Lung Database to address drug response (PLD) has been developed to support research in computer aided diagnosis (CAD). Originally established for applications involving the characterization of pulmonary nodules, the PLD has been augmented to provide initial datasets for CAD research of other diseases. In general, the best performance for a CAD system is achieved when it is trained with a large amount of well documented data. Such training databases are very expensive to create and their lack of general availability limits the targets that can be considered for CAD applications and hampers development of the CAD field. The approach taken with the PLD has been to make available small datasets together with both manual and automated documentation. Furthermore, datasets with special properties are provided either to span the range of task complexity or to provide small change repeat images for direct calibration and evaluation of CAD systems. This resource offers a starting point for other research groups wishing to pursue CAD research in new directions. It also provides an on-line reference for better defining the issues relating to specific CAD tasks.
为应对药物反应而开发的公共肺部数据库(PLD),旨在支持计算机辅助诊断(CAD)研究。PLD最初是为涉及肺结节特征描述的应用而建立的,现已得到扩充,可为其他疾病的CAD研究提供初始数据集。一般来说,CAD系统在使用大量记录完善的数据进行训练时,能达到最佳性能。创建这样的训练数据库成本非常高,而且其缺乏普遍可用性限制了CAD应用可考虑的目标,并阻碍了CAD领域的发展。PLD所采用的方法是提供小型数据集以及手动和自动文档。此外,还提供具有特殊属性的数据集,以涵盖任务复杂性范围,或提供小变化重复图像,用于CAD系统的直接校准和评估。该资源为希望在新方向上开展CAD研究的其他研究小组提供了一个起点。它还提供了一个在线参考,以便更好地界定与特定CAD任务相关的问题。