Summary
This collection consists of Computed Tomography (CT) images of the mediastinum and abdomen in which lymph node positions are marked by radiologists at the National Institutes of Health, Clinical Center. Radiologists at the I maging Biomarkers and Computer-Aided Diagnosis Laboratory labeled a total of 388 mediastinal lymph nodes in CT images of 90 patients and a total of 595 abdominal lymph nodes in 86 patients.
The collection is aimed at the medical image computing community for developing and assessing computer-aided detection methods. Automated detection of lymph nodes can be an important clinical diagnostic tool but is very challenging due to the low contrast of surrounding structures in CT and to their varying sizes, poses, shapes and sparsely distributed locations. This data set is made available to make direct comparison to other detection methods in order to advance the state of the art.
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:.
National Institutes of Health, Bethesda MD. Special thanks to Dr. Holger R. Roth and Dr. Ronald Summers, Imaging Biomarkers and Computer-Aided Diagnosis Laboratory , Grant Magnuson Clinical Center .
Data Access
| Data Type | Download all or Query/Filter | License |
|---|---|---|
| Images (DICOM, 57.8GB) |
(Download requires the NBIA Data Retriever) | |
| Med ABD Lymph Annotations (ZIP) |
| |
| Med Lymph Candidate Nodes (ZIP) |
| |
| Med ABD Lymph Masks ( ZIP) |
|
Click the Versions tab for more info about data releases.
Additional Resources for this Dataset
The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.
- Imaging Data Commons (IDC) (Imaging Data)
Detailed Description
Collection Statistics | |
|---|---|
Modalities | CT |
Number of Participants | 176 |
Number of Studies | 176 |
Number of Series | 176 |
Number of Images | 110,103 |
| Images Size (GB) | 57.8 |
The DICOM files were created from volumetric images (Analyze and NifTI) using this from ITK: http://www.itk.org/Doxygen/html/Examples_2IO_2ImageReadDicomSeriesWrite_8cxx-example.html.
Annotation files
MED_ABD_LYMPH_ANNOTATIONS.zip (new 6/24/2015). The annotations include a folder for each case with text files of voxel indices, physical coordinates, size measurements and a MITK point set file (.mps), which can be visualized using the MITK workbench (Note: only release 2014.10.0 and later supports visualization of point set files using the "point set interaction plugin"). Abdominal size measurements include the longest and shortest axis in axial view of a lymph node. The shortest axis is used for the RECIST criteria. The mediastinal set only includes the shortest axis.
Mediastinal and abdominal lymph nodes
Computer-generated candidate detections for mediastinal and abdominal lymph nodes (produced by methods in [K. Cherry et al., SPIE Med. Img. 2014] and [J. Liu et al., SPIE Med. Img. 2014]]). See attached: MED_ABD_LYMPH_CANDIDATES.zip (new 9/14/2015).
MED_ABD_LYMPH_MASKS.zip (new 12/8/2015): These files contain a compressed NifTI image (*.nii.gz) for each patient with manually traced lymph node segmentations. Note: these segmentation masks were produced independently to the centroid annotations in MED_ABD_LYMPH_ANNOTATIONS.zip. There is an overlapping set of lymph nodes marked in both files but the indexing does not align.
Please cite the following paper when using the segmentation masks:
A Seff, L Lu, A Barbu, H Roth, HC Shin, RM Summers. Leveraging Mid-Level Semantic Boundary Cues for Automated Lymph Node Detection. Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015, 53-61 (http://link.springer.com/chapter/10.1007/978-3-319-24571-3_7)
Citations & Data Usage Policy
Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:
Data Citation
Roth, H., Lu, L., Seff, A., Cherry, K. M., Hoffman, J., Wang, S., Liu, J., Turkbey, E., & Summers, R. M. (2015). A new 2.5 D representation for lymph node detection in CT [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2015.AQIIDCNM
Publication Citation
Roth, H. R., Lu, L., Seff, A., Cherry, K. M., Hoffman, J., Wang, S., Liu, J., Turkbey, E., & Summers, R. M. (2014). A New 2.5D Representation for Lymph Node Detection Using Random Sets of Deep Convolutional Neural Network Observations. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 (pp. 520–527). Springer International Publishing. https://doi.org/10.1007/978-3-319-10404-1_65
Publication Citation
Seff, A., Lu, L., Cherry, K.M., Roth, H.R., Liu, J., Wang, S., Hoffman, J., Turkbey, E.B., & Summers, R.M. 2D view aggregation for lymph node detection using a shallow hierarchy of linear classifiers. Medical Image Computing and Computer-Assisted Intervention--MICCAI 2014, p544-552, 2014. (http://arxiv.org/abs/1408.3337)
Publication Citation
Please cite the following paper when using the segmentation masks:
Seff, A., Lu, L., Barbu, A., Roth, H., Shin, H.-C., & Summers, R. M. (2015). Leveraging Mid-Level Semantic Boundary Cues for Automated Lymph Node Detection. In Lecture Notes in Computer Science Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015 (pp. 53–61). Springer International Publishing. https://doi.org/10.1007/978-3-319-24571-3_7
TCIA Citation
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 that leverage our data. At this time we are not aware of any publications based on this data. If you have a publication you'd like to add please contact the TCIA Helpdesk.
Version 4 (Current): Updated 2015/12/14
| Data Type | Download all or Query/Filter |
|---|---|
| Images (DICOM, 57.8GB) |
(Download requires the NBIA Data Retriever) |
| Med ABD Lymph Annotations (ZIP) |
|
| Med Lymph Candidate Nodes (ZIP) |
|
| Med ABD Lymph Masks (ZIP) |
|
MED_ABD_LYMPH_MASKS.zip added via the wiki.
Version 3: Updated 2015/09/14
MED_ABD_LYMPH_CANDIDATES.zip added via the wiki.
Version 2: Updated 2015/06/24
MED_ABD_LYMPH_ANNOTATIONS.zip added via the wiki.
Version 1: Updated 2015/03/16
Image data set uploaded