Radiomic analysis offers a powerful tool for the extraction of clinically relevant information
from radiologic imaging. Radiomics can be used to predict patient outcome through …

Radiomics–the high-throughput computation of quantitative image features extracted from
medical imaging modalities-can be used to aid clinical decision support systems in order to …

Historically, medical imaging has been a qualitative or semi-quantitative modality. It is
difficult to quantify what can be seen in an image, and to turn it into valuable predictive …

Radiomics, the high-throughput mining of quantitative image features from standard-of-care
medical imaging that enables data to be extracted and applied within clinical-decision …

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

Radiomics uses multiple image features from medical imaging data to predict clinical
variables. Various features can be constructed to describe the properties of the full image, or …

During the last decade, there is an increasing usage of quantitative methods in Radiology in
an effort to reduce the diagnostic variability associated with a subjective manner of …

In the past decade, the field of medical image analysis has grown exponentially, with an
increased number of pattern recognition tools and an increase in data set sizes. These …

Radiomics is a high-throughput approach to image phenotyping. It uses computer
algorithms to extract and analyze a large number of quantitative features from radiological …

Advances in both imaging and computers have synergistically led to a rapid rise in the
potential use of artificial intelligence in various radiological imaging tasks, such as risk …