Lung CT Segmentation Challenge 2017 (LCTSC)
J. Yang and G. Sharp and H. Veeraraghavan and W. van Elmpt and A. Dekker and T. Lustberg and M. Gooding

@article{,
title= {Lung CT Segmentation Challenge 2017 (LCTSC)},
doi= {10.7937/K9/TCIA.2017.3R3FVZ08},
year= {2017},
keywords= {},
author= {J. Yang and G. Sharp and H. Veeraraghavan and W. van Elmpt and A. Dekker and T. Lustberg and M. Gooding},
abstract= {Average 4DCT or free-breathing (FB) CT images from 60 patients, depending on clinical practice, are used for this challenge. Data were acquired from 3 institutions (20 each). Datasets were divided into three groups, stratified per institution:

36 training datasets
12 off-site test datasets
12 live test datasets

https://i.imgur.com/CzjcFRj.png

|Collection Statistics| |
|--- |--- |
|Image Size (GB)|4.8|
|Modalities|CT, RT|
|Number of Images|9569|
|Number of Patients|60|
|Number of Series|96|
|Number of Studies|60|

**Reference:** Yang et al., Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017. Medical Physics 2018. https://doi.org/10.1002/mp.13141 (data: https://doi.org/10.7937/K9/TCIA.2017.3R3FVZ08)},
terms= {},
license= {Creative Commons Attribution 3.0 Unported License},
superseded= {},
url= {https://wiki.cancerimagingarchive.net/display/Public/Lung+CT+Segmentation+Challenge+2017}
}