SP-0384: Radiomics for physicists – understanding feature extraction, modelling, performance validation and applications of radiomics

Applications and limitations of radiomics.

Radiomics is an emerging field in quantitative imaging that uses advanced imaging features to objectively and quantitatively describe tumour phenotypes. Radiomic features have recently drawn considerable interest due to its potential predictive power for treatment outcomes and cancer genetics, which may have important applications in personalized medicine. In this technical review, we describe ...

Radiomics: Current Challenges in Clinical Validation

Radiomics can be defined as the extraction and analysis of large amounts of advanced quantitative imaging features with high throughput from medical images obtained with various modalities [1]. Radiomics methods can be applied across various cancers to identify tumor phenotype characteristics in the images that correlate with their likelihood of survival, as well as their association with the u...

Dissimilarity-based representation for radiomics applications

Radiomics is a term which refers to the analysis of the large amount of quantitative tumor features extracted from medical images to find useful predictive, diagnostic or prognostic information. Many recent studies have proved that radiomics can offer a lot of useful information that physicians cannot extract from the medical images and can be associated with other information like gene or prot...

QuantImage: An Online Tool for High-Throughput 3D Radiomics Feature Extraction in PET-CT

The processes of radiomics consist of image-based personalized tumor phenotyping for precision medicine. They complement slow, costly, and invasive molecular analysis of tumoral tissue. Whereas the relevance of a large variety of quantitative imaging biomarkers has been demonstrated for various cancer types, most studies were based on 2D image analysis of relatively small patient cohorts. In th...

Radiomics and Deep Learning