Computer-aided diagnosis of lung cancers based on quantitative analysis of time-interval changes on thoracic CT images

肺癌是全球癌症死亡的最常见原因。CT是肺成像的首选模式，因为这种模式是目前体内肺成像最敏感的方式。一些证据表明，CT与低剂量成像协议可能会提高肺结节的敏感性相对于X线摄影。虽然这项研究确实显示了基于CT的筛查的有效性，但医生经常面临的问题是决定适当的管理策略，以最大限度地提高患者生存率和保护肺功能。本研究的重点是使用CT值直方图来表示肺结节内部结构的框架，旨在将患者分为疾病进展高风险（高风险组）和疾病进展低风险（低风险组）。

Lung cancer is the most common cause of cancer death worldwide. CT is the modality of choice for lung imaging because this modality is the most sensitive way for imaging lung in vivo currently. Some evidences suggested that CT with a low-dose imaging protocol may improve pulmonary nodule sensitivity relative to radiography. While this study does show the efficacy of CT based screening, physicians often face the problem of deciding an appropriate management strategies for maximizing patient survival and preserving lung function. This study focuses on a framework within which CT value histograms is used to represent internal structures of pulmonary nodules, aiming at classifying patients between those at high risk of disease progression (high-risk group) and those at low risk of disease progression (low-risk group).