Published on 01 January 2022
LUMIERE dataset - Pyradiomics features based on HD-GLIO-AUTO segmentations
View DatasetSuter, Yannick;Knecht, Urspeter;Valenzuela, Waldo;Notter, Michelle;Hewer, Ekkehard;Schucht, Philippe;Wiest, Roland;Reyes, Mauricio
Description
This CSV contains the radiomic features extracted for all study dates where all four MRI sequences and automated segmentation from HD-GLIO-AUTO are available. The features were extracted from the images resampled to atlas space. Please note that features could not be extracted for studies where a given segmentation label was not found (or too small, see the minimum ROI size in the settings column). See our GitHub repository for a script to customize the extraction.
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Publication Details
Subfield
Radiology, Nuclear Medicine and Imaging
Field
Medicine
Domain
Health Sciences
Confidence Score
55%
Source
Scholar Data Model
Keywords
Artificial Intelligence and Image ProcessingFOS: Computer and information sciences110320 Radiology and Organ ImagingFOS: Clinical medicine