Title: Assessing radiomic feature robustness to interpolation in 18F-FDG PET imaging - data
Citation
Whybra P, Parkinson C, Foley K, et al. (2019). Assessing radiomic feature robustness to interpolation in 18F-FDG PET imaging - data. Cardiff University. https://doi.org/10.17035/d.2019.0078762440
Access Rights: Data is provided under a Creative Commons Attribution (CC BY 4.0) licence
Access Method: https://doi.org/10.17035/d.2019.0078762440 will take you to the repository page for this dataset, where you will be able to download the data or find further access information, as appropriate.
Cardiff University Dataset Creators
Dataset Details
Publisher: Cardiff University
Date (year) of data becoming publicly available: 2019
Data format: .csv
Estimated total storage size of dataset: Less than 100 megabytes
Number of Files In Dataset: 24
DOI : 10.17035/d.2019.0078762440
DOI URL: http://doi.org/10.17035/d.2019.0078762440
A set of feature extraction results used to assess feature robustness to interpolation in 18F-FDG PET imaging. Morphological, first-order, and texture features (n=141), were extracted from segmented tumour volumes. Patients had biopsy-proven oesophageal cancer and had undergone PET/CT imaging as part of staging. Data is from 441 patients, split (80%/20%) into testing (n=353) and validation (n=88) dataset. Both linear and spline interpolation methods were explored. Features were extracted after interpolation to 6 different isotropic voxel sizes (1.5mm, 1.8mm, 2.0mm, 2.2mm, 2.5mm, 2.7mm). Each csv file relates to a specific interpolation method, dataset type (testing or validation), and voxel size. Research results using this data published at DOI: 10.1038/s41598-019-46030-0 Supplementary materials with feature list and criteria available at DOI: 10.1038/s41598-019-46030-0.
Description
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