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The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

机译:肺图像数据库协会(LIDC)和图像数据库资源倡议(IDRI):CT扫描中完整的肺结节参考数据库

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摘要

>Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.>Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC∕IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (“nodule≥3 mm,” “nodule<3 mm,” and “non-nodule≥3 mm”). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus.>Results: The Database contains 7371 lesions marked “nodule” by at least one radiologist. 2669 of these lesions were marked “nodule≥3 mm” by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings.>Conclusions: The LIDC∕IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.
机译:>目的:通过功能齐全的计算机断层扫描(CT)扫描库,可以促进用于肺结节检测,分类和定量评估的计算机辅助诊断(CAD)方法的开发。肺图像数据库协会(LIDC)和图像数据库资源计划(IDRI)完成了这样的数据库,为医学影像研究界建立了可公开获得的参考。由美国国立癌症研究所(NCI)发起,并由美国国立卫生研究院(FNIH)基金会进一步推动,并在食品药品监督管理局(FDA)的积极参与下,这种公私合作伙伴关系证明了一项成功的研究成果。财团建立在基于共识的流程上。>方法:七个学术中心和八家医学影像公司合作,共同确定,解决和解决具有挑战性的组织,技术和临床问题,从而为稳健发展奠定坚实的基础数据库。 LIDC ∕ IDRI数据库包含1018个病例,每个病例都包括来自临床胸部CT扫描的图像和相关的XML文件,该文件记录了由四名经验丰富的胸部放射科医生进行的两阶段图像注释过程的结果。在最初的盲读阶段,每个放射线医师独立检查每次CT扫描并标记属于以下三类之一的病变(“结节≥3mm”,“结节<3 mm”和“非结节≥3mm”)。在随后的非盲读阶段,每个放射线医生独立地审查自己的标记以及其他三位放射线医生的匿名标记以得出最终意见。此过程的目标是在每次CT扫描中尽可能完全地识别所有肺结节,而无需强制共识。>结果:数据库包含至少由一名放射科医生标记为“结节”的7371个病变。至少一名放射科医生将其中2669个病变标记为“结节≥3mm”,其中有928名(34.7%)从所有四位放射科医生那里获得了此类标记。这2669个病变包括结节轮廓和主观结节特征等级。

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