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 - dataCardiff Universityhttps://doi.org/10.17035/d.2019.0078762440



Access RightsData 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.


Dataset Details

PublisherCardiff University

Date (year) of data becoming publicly available2019

Data format.csv

Estimated total storage size of datasetLess than 100 megabytes

Number of Files In Dataset24

DOI 10.17035/d.2019.0078762440

DOI URLhttp://doi.org/10.17035/d.2019.0078762440


Description

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.


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Last updated on 2022-29-04 at 14:42