...
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.
Studies Studies that have used this collection include the following (Please cite in any publications resulting from using this data):
@incollection{roth2014new,
title={A new 2.5 D representation for lymph node detection using random sets of deep convolutional neural network observations},
...
| Info | ||
|---|---|---|
| ||
|
...
|
...
pages={520--527},
year={2014},
publisher={Springer}
}
@incollection{seff20142d,
title={2D view aggregation for lymph node detection using a shallow hierarchy of linear classifiers},
...
|
...
|
...
|
...
|
year={2014},
publisher={Springer}
}
...
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
Imaging Data
| Info |
|---|
You can view and download these images on TCIA by clicking |
Collection Statistics | (updated 2015/03/16) |
|---|---|
Modalities | CT |
Number of Patients | 176 |
Number of Studies | 176 |
Number of Series | 176 |
Number of Images | 110,103 |
| Images Size (GB) | 57.8 |
If you are unsure how to download this collection, please view Searching by Collection or refer to TCIA's User's Guide for more detailed instructions on using the site.
Related Data
Annotation files: MED_ABD_LYMPH_ANNOTATIONS.zip . The annotations include a folder for each case with text files of voxel indices, physical coordinates 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").
The DICOM files were created from volumetric images (Analyze and NifTI) using this from ITK:
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....