Published on 01 January 2022

LUMIERE dataset - Pyradiomics features based on HD-GLIO-AUTO segmentations

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Suter, 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.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.3

FAIR Score

13%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

Assigned Domain

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

Normalization Factors

FT

15.38

CTw

1.00

MTw

1.00