DICOM-SEG Conversions for TCGA-LGG and TCGA-GBM Segmentation Datasets (DICOM-Glioma-SEG)

Description

This dataset contains DICOM-SEG (DSO) conversions of the  Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-LGG collection  and  Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-GBM collection analysis datasets.
 
The MR volumes and segmentations provided in the original segmentation datasets (T1 pre-contrast, T1 post-contrast, T2, FLAIR) are in NIfTI format, co-registered to an atlas space, and re-sampled to 1mm isotropic resolution. This dataset contains DICOM-SEG versions of the same segmentations, transformed back into the original patient resolutions and orientations found in the TCIA’s TCGA-GBM and TCGA-LGG datasets. This allows users to extract features from MR sequences without introducing interpolation artifacts from isotropic resampling.
 
The process for creating these DSO objects is as follows. Patient data from the original NIfTI datasets were registered and resampled from isotropic space to patient space and resolution using  3DSlicer’s BRAINSFit module . The affine transformation files from these registrations are used to register and resample both the semi-automatic and automatic NIfTI segmentations into the spaces of each original MR DICOM dataset. These transformed NIfTI segmentations are then converted into DICOM-SEG datasets using the software package  dcmqi . Because each MR sequence has a unique patient space and resolution, the resulting dataset contains four DSO segmentations for each original NIfTI segmentation.

Included in this dataset are the converted DSO volumes, DSO metadata values used in the DSO conversion program dcmqi, and affine transformation files from isotropic space to the original patient space saved in ITK format. Original patient DICOM volumes are also available for download below. A key is provided that maps individual DSO objects to their corresponding DICOM Series UID, to facilitate easier data analysis.