影像组学系列视频教程
Video tutorial series

由中科院博士/浙江大学医学院博士后李任远倾情呈现
Presented by Li-RY, Postdoctoral of Affiliated Hospital of Zhejiang University.

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影像组学工具平台
Platform of Radiomics

由田捷教授领导的中国科学院分子影像重点实验室开发的影像组学科研工具平台
Radiomics can provide powerful tools for cancer diagnosis and prognosis.

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影像组学工具包
Extensions for Radiomics

最流行、强有力的影像组学特征提取与特征分析工具
Powerful & popular tools for radiomics feature extraction and analysis.

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Typical Paper

有一些关于影像组学的案例和研究，展示了影像组学作为个体化治疗的有力工具的临床潜力。
There are some cases and reaserch about Radiomics, which providing a demonstration of the clinical potential of radiomics as a powerful to for personalized therapy.

CT 筛查预测恶性结节
Predicting malignant nodules from screening CTs

对确诊肺癌患者的随访低剂量CT筛查的影像进行定量分析，研究是否可以预测随后癌症的出现（即基于影像组学的肺结节良恶性鉴别）。
Determine if quantitative analyses (“radiomics”) of low dose CT lung cancer screening images at baseline can predict subsequent emergence of cancer.

doi: 10.1016/j.jtho.2016.07.002

肺癌的影像组学特征提取
Radiomic Features Extracted From Lung Cancer

评估从肺癌瘤周区域提取的CT影像组学特征的稳定性和可重复性，并探讨其临床实际应用及相关领域的研究现状。
Assess the stability and reproducibility of CT radiomic features extracted from the peritumoral regions of lung lesions.

doi: 10.1002/mp.13808

影像组学技术的应用及其局限性
Applications and limitations of radiomics

回顾影像组学领域和有关的技术问题，分析影像组学领域的研究设计实践。
Review radiomic application areas and technical issues, as well as proper practices for the designs of radiomic studies.

doi: 10.1088/0031-9155/61/13/R150

基于CT的影像组学特征预测肺腺癌远处转移
CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma

评估CT影像组学特征预测肺腺癌患者远处转移模型的能力。
Evaluates CT radiomic features for their capability to predict distant metastasis for lung adenocarcinoma patients.

doi: 10.1016/j.radonc.2015.02.015