Fused feature signatures to probe tumour radiogenomics relationships.

ABSTRACT: Radiogenomics relationships (RRs) aims to identify statistically significant correlations between medical image features and molecular characteristics from analysing tissue samples. Previous radiogenomics studies mainly relied on a single category of image feature extraction techniques (ETs); these are (i) handcrafted ETs that encompass visual imaging characteristics, curated from knowledge of human experts and, (ii) deep ETs that quantify abstract-level imaging characteristics from large data. Prior studies therefore failed to leverage the complementary information that are accessible from fusing the ETs. In this study, we propose a fused feature signature (FF_Sig): a selection of image features from handcrafted and deep ETs (e.g., transfer learning and fine-tuning of deep learn

SUBMITTER: Xia T 

PROVIDER: S-EPMC8828715 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature