The volume, variety, and velocity of medical imaging data are exploding, making it impractical for clinicians to properly utilize such available information resources in an efficient fashion. At the same time, the interpretation of such a large amount of medical imaging data by humans is significantly error prone, reducing the possibility of extracting informative data. The ability to process such large amounts of data promises to decipher encrypted information within medical images, develop predictive and prognosis models to design personalized diagnosis, allow comprehensive study of tumor phenotype, and allow the assessment of tissue heterogeneity for diagnosis of different types of cancers.

中文翻译：

---

肺癌放射组学：2018 年 IEEE 视频和图像处理杯学生竞赛亮点 [SP 竞赛]

医学成像数据的数量、种类和速度正在呈爆炸式增长，使得临床医生以有效的方式正确利用此类可用信息资源变得不切实际。同时，人类对如此大量的医学成像数据的解释很容易出错，从而降低了提取信息数据的可能性。处理如此大量数据的能力有望破译医学图像中的加密信息，开发预测和预后模型来设计个性化诊断，允许对肿瘤表型进行全面研究，并允许评估组织异质性以诊断不同类型的癌症。