1. Image Preprocessing and Filtering Effect on the Estimate of Myocardial Radiomic Features From T1 and T2 Mapping in Hypertrophic Cardiomyopathy
- Author
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Marco Giannelli, Alessio Lilli, Mario Mascalchi, Giancarlo Casolo, Riccardo Lazzarini, Andrea Barucci, Chiara Marzi, Rita Borgheresi, A. C. Traino, Luca Salvatori, Stefano Diciotti, Daniela Marfisi, Jacopo Del Meglio, Stefania Linsalata, Claudio Vignali, and Carlo Tessa more...
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business.industry ,Computer science ,T2 mapping ,Hypertrophic cardiomyopathy ,medicine ,Preprocessor ,Pattern recognition ,Artificial intelligence ,business ,medicine.disease ,Image (mathematics) - Abstract
Radiomics is emerging as a promising and useful tool in cardiac magnetic resonance (CMR) imaging applications. Accordingly, the purpose of this study was to investigate, for the first time, the effect of image preprocessing and filtering on radiomic features estimation from quantitative CMR T1 and T2 mapping. Specifically, T1 and T2 maps of 26 patients with hypertrophic cardiomyopathy (HCM) were used to estimate 98 radiomic features for 7 different resampling voxel sizes (at fixed bin width), 9 different bin widths (at fixed resampling voxel size), and 7 different spatial filters (at fixed resampling voxel size/bin width). While we found a remarkable dependence of myocardial radiomic features from T1 and T2 mapping on image filters, many radiomic features showed a limited sensitivity to resampling voxel size/bin width, in terms of intraclass correlation coefficient (>0.75) and coefficient of variation ( more...
- Published
- 2021
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