Radiomics in medical imaging—“how-to” guide and critical reflection
Radiomics is a quantitative approach to medical imaging, which aims at enhancing the
existing data available to clinicians by means of advanced mathematical analysis. Through …
existing data available to clinicians by means of advanced mathematical analysis. Through …
Deep learning in medical imaging and radiation therapy
The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
LIFEx: a freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterization of tumor heterogeneity
Textural and shape analysis is gaining considerable interest in medical imaging, particularly
to identify parameters characterizing tumor heterogeneity and to feed radiomic models …
to identify parameters characterizing tumor heterogeneity and to feed radiomic models …
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 …
to objectively and quantitatively describe tumour phenotypes. Radiomic features have …
Artificial intelligence and machine learning in cancer imaging
An increasing array of tools is being developed using artificial intelligence (AI) and machine
learning (ML) for cancer imaging. The development of an optimal tool requires …
learning (ML) for cancer imaging. The development of an optimal tool requires …
[HTML][HTML] Repeatability and reproducibility of radiomic features: a systematic review
Purpose An ever-growing number of predictive models used to inform clinical decision
making have included quantitative, computer-extracted imaging biomarkers, or “radiomic …
making have included quantitative, computer-extracted imaging biomarkers, or “radiomic …
CT texture analysis: definitions, applications, biologic correlates, and challenges
This review discusses potential oncologic and nononcologic applications of CT texture
analysis (CTTA CT texture analysis), an emerging area of “radiomics” that extracts, analyzes …
analysis (CTTA CT texture analysis), an emerging area of “radiomics” that extracts, analyzes …
Statistical significance: p value, 0.05 threshold, and applications to radiomics—reasons for a conservative approach
G Di Leo, F Sardanelli - European radiology experimental, 2020 - Springer
Here, we summarise the unresolved debate about p value and its dichotomisation. We
present the statement of the American Statistical Association against the misuse of statistical …
present the statement of the American Statistical Association against the misuse of statistical …
Machine and deep learning methods for radiomics
Radiomics is an emerging area in quantitative image analysis that aims to relate large‐scale
extracted imaging information to clinical and biological endpoints. The development of …
extracted imaging information to clinical and biological endpoints. The development of …
Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives
MR Chetan, FV Gleeson - European radiology, 2021 - Springer
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 …
the potential to characterise tumour phenotype. The radiomics approach has the capacity to …