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 …
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 …
Fusion-based tensor radiomics using reproducible features: application to survival prediction in head and neck cancer
MR Salmanpour, M Hosseinzadeh, SM Rezaeijo… - Computer Methods and …, 2023 - Elsevier
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 …
[HTML][HTML] Radiomics and artificial intelligence for precision medicine in lung cancer treatment
Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …
[HTML][HTML] Radiomics feature reliability assessed by intraclass correlation coefficient: a systematic review
Radiomics research is rapidly growing in recent years, but more concerns on radiomics
reliability are also raised. This review attempts to update and overview the current status of …
reliability are also raised. This review attempts to update and overview the current status of …
Foundation model for cancer imaging biomarkers
Foundation models in deep learning are characterized by a single large-scale model trained
on vast amounts of data serving as the foundation for various downstream tasks. Foundation …
on vast amounts of data serving as the foundation for various downstream tasks. Foundation …
Radiomics: a primer on high-throughput image phenotyping
Radiomics is a high-throughput approach to image phenotyping. It uses computer
algorithms to extract and analyze a large number of quantitative features from radiological …
algorithms to extract and analyze a large number of quantitative features from radiological …
Oncologic imaging and radiomics: a walkthrough review of methodological challenges
Simple Summary Radiomics could increase the value of medical images for oncologic
patients, allowing for the identification of novel imaging biomarkers and building prediction …
patients, allowing for the identification of novel imaging biomarkers and building prediction …
Feature selection methods and predictive models in CT lung cancer radiomics
G Ge, J Zhang - Journal of applied clinical medical physics, 2023 - Wiley Online Library
Radiomics is a technique that extracts quantitative features from medical images using data‐
characterization algorithms. Radiomic features can be used to identify tissue characteristics …
characterization algorithms. Radiomic features can be used to identify tissue characteristics …
[HTML][HTML] A systematic review and quality of reporting checklist for repeatability and reproducibility of radiomic features
Abstract Background and Purpose Although quantitative image biomarkers (radiomics)
show promising value for cancer diagnosis, prognosis, and treatment assessment, these …
show promising value for cancer diagnosis, prognosis, and treatment assessment, these …