Journal: Tomography
Article Title: A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease
doi: 10.3390/tomography10090108
Figure Lengend Snippet: Imaging and radiomics methodology.
Article Snippet: Kafouris et al. [ ] , PET/CT using 0.14 mCi/kg 18 F-FDG , Adherence to radiomics guidelines: features extracted according to IBSI guidelines Feature extraction software: in-house software based on Matlab platform (Version 9.3, Matlab R2017b, Natick, MA, USA) , Segmentation: manual segmentation around the carotid artery wall Features extracted: first order, GLCM, GLRLM, GLSZM and NGTDM Machine learning techniques: univariate logistic regression , Performance assessment: AUC from the ROC Internal validation: bootstrapping generating 200 bootstrap samples No external validation.
Techniques: Imaging, Extraction, Software, Biomarker Discovery, Construct, Activity Assay