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

肺癌是全球最常见的癌症死亡原因。CT是目前最灵敏的活体肺成像方法，因此CT是肺部成像的首选方法。一些证据表明，CT结合低剂量成像方案可以提高肺结节相对于X线的敏感性。虽然这项研究确实显示了基于CT的筛查的有效性，但医生经常面临着决定适当的管理策略以最大化患者生存和保护肺功能的问题。本研究的重点是利用CT值直方图表示肺结节内部结构的框架，旨在对疾病进展的高危人群(高危组)和疾病进展的低危人群(低危组)进行分类。

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).