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- W3202105864 abstract "Radiomics is a rapidly evolving field within oncology. It explores the extraction of quantitativefeatures from medical scans to aid in diagnosis, prognosis and monitoring of disease. In effect,these features may act as imaging biomarkers. Radiomics is a potential piece of a multifaceteddata puzzle, powering precision medicine approaches, where treatment strategies could be tailored more to the individual than relying on a one-size-fits-all strategy. However, there are crucialchallenges within the field regarding reproducibility and reliability of many common radiomicfeatures. This thesis explored the hypothesis that varying but valid approaches to engineeredfeature extraction can cause discrepancy that harms identification and validation of potential radiomic biomarkers. As a research community, we require guidelines, standards and references tosee forward progression and to avoid a replication crisis. Through development of radiomics software, results from this work significantly contributed to a large collaborative consensus benchmarking effort to address this standardisation need. This work investigated the effect of implementation choices on compliance to this new standard. Alongside this, the role of interpolation inradiomics became a key focus through the lens of robustness. Optimal feature extraction shouldavoid redundancy and utilise robust features. Finally, benchmarking methodology and tools weredeveloped in an effort to standardise the application of filters in image processing steps prior tofeature extraction. Discrepancies between radiomics software were identified and evaluated using these tools. The uncertainties in developing optimal and robust radiomic imaging biomarkersthat result in clinically useful models are discussed." @default.
- W3202105864 created "2021-10-11" @default.
- W3202105864 creator A5012711051 @default.
- W3202105864 date "2021-07-01" @default.
- W3202105864 modified "2023-09-23" @default.
- W3202105864 title "Standardisation and optimisation of radiomic techniques for the identification of robust imaging biomarkers in oncology" @default.
- W3202105864 hasPublicationYear "2021" @default.
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