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 …
[HTML][HTML] The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges
Medical imaging can assess the tumor and its environment in their entirety, which makes it
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …
Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study
S Peng, Y Liu, W Lv, L Liu, Q Zhou, H Yang… - The Lancet Digital …, 2021 - thelancet.com
Background Strategies for integrating artificial intelligence (AI) into thyroid nodule
management require additional development and testing. We developed a deep-learning AI …
management require additional development and testing. We developed a deep-learning AI …
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 …
[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 …
Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling
Modern medicine is reliant on various medical imaging technologies for non-invasively
observing patients' anatomy. However, the interpretation of medical images can be highly …
observing patients' anatomy. However, the interpretation of medical images can be highly …
Radiomics of CT features may be nonreproducible and redundant: influence of CT acquisition parameters
R Berenguer, MDR Pastor-Juan, J Canales-Vázquez… - Radiology, 2018 - pubs.rsna.org
Purpose To identify the reproducible and nonredundant radiomics features (RFs) for
computed tomography (CT). Materials and Methods Two phantoms were used to test RF …
computed tomography (CT). Materials and Methods Two phantoms were used to test RF …
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 …
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 …
[PDF][PDF] Reproducibility and generalizability in radiomics modeling: possible strategies in radiologic and statistical perspectives
Radiomics, which involves the use of high-dimensional quantitative imaging features for
predictive purposes, is a powerful tool for develo** and testing medical hypotheses …
predictive purposes, is a powerful tool for develo** and testing medical hypotheses …