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 …
A review in radiomics: making personalized medicine a reality via routine imaging
J Guiot, A Vaidyanathan, L Deprez… - Medicinal research …, 2022 - Wiley Online Library
Radiomics is the quantitative analysis of standard‐of‑care medical imaging; the information
obtained can be applied within clinical decision support systems to create diagnostic …
obtained can be applied within clinical decision support systems to create diagnostic …
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: the facts and the challenges of image analysis
Radiomics is an emerging translational field of research aiming to extract mineable high-
dimensional data from clinical images. The radiomic process can be divided into distinct …
dimensional data from clinical images. The radiomic process can be divided into distinct …
Deep learning predicts lung cancer treatment response from serial medical imaging
Purpose: Tumors are continuously evolving biological systems, and medical imaging is
uniquely positioned to monitor changes throughout treatment. Although qualitatively tracking …
uniquely positioned to monitor changes throughout treatment. Although qualitatively tracking …
Radiomics: the bridge between medical imaging and personalized medicine
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 …
medical imaging that enables data to be extracted and applied within clinical-decision …
[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 …
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 …
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 …
[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 …