Predicting cancer outcomes with radiomics and artificial intelligence in radiology
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 …
application of AI-based cancer imaging analysis to address other, more complex, clinical …
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 …
The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenoty**
Background Radiomic features may quantify characteristics present in medical imaging.
However, the lack of standardized definitions and validated reference values have …
However, the lack of standardized definitions and validated reference values have …
CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII
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 …
current use is mostly limited to academic research, without applications in routine clinical …
Radiomics in breast cancer classification and prediction
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 …
usually performed through different imaging modalities such as mammography, magnetic …
Image biomarker standardisation initiative
The image biomarker standardisation initiative (IBSI) is an independent international
collaboration which works towards standardising the extraction of image biomarkers from …
collaboration which works towards standardising the extraction of image biomarkers from …
Fusion-based tensor radiomics using reproducible features: application to survival prediction in head and neck cancer
Background Numerous features are commonly generated in radiomics applications as
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …
Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics
YS Choi, S Bae, JH Chang, SG Kang, SH Kim… - Neuro …, 2021 - academic.oup.com
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 …
We aimed to predict the IDH status of gliomas from preoperative MR images using a fully …
Making radiomics more reproducible across scanner and imaging protocol variations: a review of harmonization methods
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 …
quantitative features used for clinical decision support. However, these radiomic features are …
Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis
A Zwanenburg - European journal of nuclear medicine and molecular …, 2019 - Springer
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 …
multicentre settings is an important criterion for clinical translation. We therefore performed a …