Plausibility and redundancy analysis to select FDG-PET textural features in non-small cell lung cancer.

ABSTRACT:

Background

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.

Materials and methods

The proposed selection procedure consists of several steps. A priori, we only include featur

SUBMITTER: Pfaehler E 

PROVIDER: S-EPMC7985880 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature