Localtab |
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active | true |
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title | Data Access |
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| Data AccessClick the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever . Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.
Data Type | Download all or Query/Filter |
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Images and Radiation Therapy Structures (DICOM, 26 GB) | Tcia button generator |
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label | Search |
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url | https://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=Vestibular-Schwannoma-SEG |
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Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/Vestibular-Schwannoma-SEG%20Feb%202021%20manifest.tcia?api=v2 |
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| Directory names mapping to modality (.csv) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/DirectoryNamesMappingModality.csv?api=v2 |
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| Registration Matrices (.tfm, zip, 257 KB) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/Vestibular-Schwannoma-SEG_matrices%20Mar%202021.zip?api=v2 |
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| Contours (JSON, zip, 16.7 MB) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/Vestibular-Schwannoma-SEG%20contours%20Mar%202021.zip?api=v2 |
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| Click the Versions tab for more info about data releases. |
Localtab |
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title | Detailed Description |
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| Detailed Description | |
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Modalities | MR, RTSTRUCT, RTDOSE, RTPLAN | Number of Participants | 242 | Number of Studies | 242 | Number of Series | 1936 | Number of Images | 48582 | Images Size (GB) | 26 |
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Localtab |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy Tcia license 4 international |
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Info |
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| Shapey, J., Kujawa, A., Dorent, R., Wang, G., Bisdas, S., Dimitriadis, A., Grishchuck, D., Paddick, I., Kitchen, N., Bradford, R., Saeed, S., Ourselin, S., & Vercauteren, T. (2021). Segmentation of Vestibular Schwannoma from Magnetic Resonance Imaging: An Open Annotated Dataset and Baseline Algorithm [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.9YTJ-5Q73 |
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title | Publication Citation |
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| Shapey, J., Wang, G., Dorent, R., Dimitriadis, A., Li, W., Paddick, I., Kitchen, N., Bisdas, S., Saeed, S. R., Ourselin, S., Bradford, R., & Vercauteren, T. (2021). An artificial intelligence framework for automatic segmentation and volumetry of vestibular schwannomas from contrast-enhanced T1-weighted and high-resolution T2-weighted MRI. Journal of Neurosurgery, 134(1), 171–179. https://doi.org/10.3171/2019.9.jns191949 |
Info |
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| Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. Journal of Digital Imaging, 26(6), 1045–1057. https://doi.org/10.1007/s10278-013-9622-7 |
Other Publications Using This Data TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk. |
Localtab |
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| Version 2 (Current): Updated 2021/03/15 Data Type | Download all or Query/Filter |
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Images and Radiation Therapy Structures (DICOM, 26 GB) | Tcia button generator |
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label | Search |
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url | https://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=Vestibular-Schwannoma-SEG |
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Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/Vestibular-Schwannoma-SEG%20Feb%202021%20manifest.tcia?api=v2 |
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| Directory names mapping to modality (.csv) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/DirectoryNamesMappingModality.csv?api=v2 |
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| Registration Matrices (.tfm, zip, 257 KB) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/Vestibular-Schwannoma-SEG_matrices%20Mar%202021.zip?api=v2 |
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| Contours (JSON, zip, 16.7 MB) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/Vestibular-Schwannoma-SEG%20contours%20Mar%202021.zip?api=v2 |
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| JSON contours and registration matrices: Registration Matrices: For each subject and each modality a text file named inv_T1_LPS_to_T2_LPS.tfm or inv_T2_LPS_to_T1_LPS.tfm was added. The files specify affine transformation matrices that can be used to co-register the T1 image to the T2 image and vice versa. The file format is a standard format defined by the Insight Toolkit (ITK) library. The matrices are the result of the co-registration of fiducials of the Leksell Stereotactic System MR Indicator box into which the patient’s head is fixed during image acquisition. The localization of fiducials and co-registration was performed automatically by the LeksellGammaPlan software.Contours: For each subject and each modality a text file named contours.json was added. The contour files in the T1 and T2 folder contain the contour points of the segmented structures in JavaScript Object Notation (JSON) format, mapped in the coordinate frames of the T1 image and the T2 image, respectively. There can be small differences between the contour points of the RTSTRUCT and the contour points of the JSON files as explained in the following: In most cases, the tumour was segmented on the T1 image while the cochlea was typically segmented on the T2 image. This meant that some contour lines (typically for the tumour) were coplanar with the slices of the T1 image while others (typically for the cochlea) were coplanar with T2 slices. After co-registration, the (un-resampled) slices of the T1 and T2 image generally did not coincide, e.g., due to different image position and, occasionally, slice thickness. Therefore, the combined co-registered contour lines were neither jointly coplanar with the T1 nor with the T2 image slices. Upon export of the segmentations in a given target space, the LeksellGammaPlan software interpolates between the original contour lines to create new slice-aligned contour lines in the target image space (T1 or T2). This results in the interpolated slice-aligned contour lines found in the RTSTRUCTs. In contrast, the contours in the JSON files were not interpolated after co-registration, and therefore describe the original (potentially off-target-space-slice) manual segmentation accurately.The github repository (https://github.com/KCL-BMEIS/VS_Seg) contains a script that performs co-registration based on the .tfm files and creates binary segmentation files in NIFTI format based on the JSON filesmatrices & contours added. Version 1: Updated 2021/02/26 Data Type | Download all or Query/Filter |
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Images and Radiation Therapy Structures (DICOM, 26 GB) | Tcia button generator |
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label | Search |
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url | https://nbia.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=Vestibular-Schwannoma-SEG |
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Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/Vestibular-Schwannoma-SEG%20Feb%202021%20manifest.tcia?api=v2 |
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| Directory names mapping to modality (.csv) | Tcia button generator |
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url | https://wiki.cancerimagingarchive.net/download/attachments/70229053/DirectoryNamesMappingModality.csv?api=v2 |
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