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  • A new 2.5 D representation for lymph node detection in CT (CT Lymph Nodes)

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titleReferences
  • Roth, Holger R and Lu, Le and Seff, Ari and Cherry, Kevin M and Hoffman, Joanne and Wang, Shijun and Liu, Jiamin and Turkbey, Evrim and Summers, Ronald M. A new 2.5 D representation for lymph node detection using random sets of deep convolutional neural network observations. Medical Image Computing and Computer-Assisted Intervention--MICCAI 2014, p520-527, 2014. (link)
  • Seff, Ari and Lu, Le and Cherry, Kevin M and Roth, Holger R and Liu, Jiamin and Wang, Shijun and Hoffman, Joanne and Turkbey, Evrim B and Summers, Ronald 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. (link)
  • The Digital Object Identifier http://dx.doi.org/10.7937/K9/TCIA.2015.AQIIDCNM should also be used to refer to this data set.

Acknowledgements

We would like to acknowledge the individuals and institutions that have provided data for this collection:.

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You can view and download these images on TCIA by clicking  and selecting the CT Lymph Nodes collection. You can also access the data via it's Digital Object Identifier page: http://dx.doi.org/10.7937/K9/TCIA.2015.AQIIDCNM.

 

 

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 (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.

The DICOM files were created from volumetric images (Analyze and NifTI) using this from ITK: