The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the
application of AI-based cancer imaging analysis to address other, more complex, clinical …

Objectives Radiomics is the extraction of quantitative data from medical imaging, which has
the potential to characterise tumour phenotype. The radiomics approach has the capacity to …

Even though radiomics can hold great potential for supporting clinical decision-making, its
current use is mostly limited to academic research, without applications in routine clinical …

Background Radiomic features may quantify characteristics present in medical imaging.
However, the lack of standardized definitions and validated reference values have …

Breast Cancer (BC) is the common form of cancer in women. Its diagnosis and screening are
usually performed through different imaging modalities such as mammography, magnetic …

Background Numerous features are commonly generated in radiomics applications as
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …

Background Glioma prognosis depends on isocitrate dehydrogenase (IDH) mutation status.
We aimed to predict the IDH status of gliomas from preoperative MR images using a fully …

Radiomics converts medical images into mineable data via a high-throughput extraction of
quantitative features used for clinical decision support. However, these radiomic features are …

Over the last decade there has been an extensive evolution in the Artificial Intelligence (AI)
field. Modern radiation oncology is based on the exploitation of advanced computational …

Radiomics in nuclear medicine is rapidly expanding. Reproducibility of radiomics studies in
multicentre settings is an important criterion for clinical translation. We therefore performed a …