Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive
biopsy based molecular assays but gives huge potential for medical imaging, which has the …

Human cancers exhibit strong phenotypic differences that can be visualized noninvasively
by medical imaging. Radiomics refers to the comprehensive quantification of tumour …

The early detection of relapse following primary surgery for non-small-cell lung cancer and
the characterization of emerging subclones, which seed metastatic sites, might offer new …

Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated
remarkable progress in image-recognition tasks. Methods ranging from convolutional neural …

“Radiomics” refers to the extraction and analysis of large amounts of advanced quantitative
imaging features with high throughput from medical images obtained with computed …

Radiomics aims to quantify phenotypic characteristics on medical imaging through the use
of automated algorithms. Radiomic artificial intelligence (AI) technology, either based on …

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

… Hugo JWL Aerts PhD … Hugo JWL Aerts PhD … Hugo JWL Aerts reports shares from
Genospace and Sphera, outside of thesubmitted work. The remaining authors made no disclosures. …

Radiomics is an emerging field in quantitative imaging that uses advanced imaging features
to objectively and quantitatively describe tumour phenotypes. Radiomic features have …

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs
used daily in oncology include clinical TNM stage, objective response and left ventricular …