Addressing challenges in radiomics research: systematic review and repository of open-access cancer imaging datasets.

ABSTRACT:

Objectives

Open-access cancer imaging datasets have become integral for evaluating novel AI approaches in radiology. However, their use in quantitative analysis with radiomics features presents unique challenges, such as incomplete documentation, low visibility, non-uniform data formats, data inhomogeneity, and complex preprocessing. These issues may cause problems with reproducibility and standardization in radiomics studies.

Methods

We systematically reviewed imaging datasets with public copyright licenses, published up to March 2023 across four large online cancer imaging archives. We included only datasets with tomographic images (CT, MRI, or PET), segmentations, and clinical annotations, specifically identifying those suitable for radiomics research. Reproducible prepro

SUBMITTER: Woznicki P 

PROVIDER: S-EPMC10716101 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature