Radiomics refers to the extraction of a large number of image biomarker describing the tumor phenotype displayed in a medical image. Extracted from positron emission tomography (PET) images, radiomics showed diagnostic and prognostic value for several cancer types. However, a large number of radiomic features are nonreproducible or highly correlated with conventional PET metrics. Moreover, radiomic features used in the clinic should yield relevant information about tumor texture. In this study, we propose a framework to identify technical and clinical meaningful features and exemplify our results using a PET non‐small cell lung cancer (NSCLC) dataset.

中文翻译：

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在非小细胞肺癌中选择FDG-PET纹理特征的似真性和冗余分析

放射线学是指提取描述医学图像中显示的肿瘤表型的大量图像生物标志物。从正电子发射断层扫描（PET）图像中提取的放射性化合物显示出对几种癌症类型的诊断和预后价值。然而，大量的放射学特征是不可再现的或与常规PET指标高度相关。此外，临床中使用的放射学特征应能得出有关肿瘤质地的相关信息。在这项研究中，我们提出了一个框架，用于识别技术和临床有意义的特征，并使用PET非小细胞肺癌（NSCLC）数据集来例证我们的结果。