Welcome to the CT segmentation challenge

Moist Run

Last update: 3/28/2013 05:30 PM EST

The goal of the CT segmentation challenge is to compare the bias (where possible) and repeatability of automatic, semi-automatic and manual segmentations for lung CT studies. In this phase, investigators from Columbia, MGH, Moffitt and Stanford have identified 50 lung CT nodules and made available the data in DICOM format. Algorithm developers and users are requested to submit at least 4 repetitions of their algorithm for each nodule. We are quite flexible in accepting a variety of image formats for the segmentation volumes. We have experience with NIFTI, NRRD, JPG, PNG, DICOM-SEG, DICOM-RT, AIM, and LIDC-XML. If you would like to submit segmentations in a format other than one of these, please contact Jayashree at kalpathy@nmr.mgh.harvard.edu.

Data description:

We have 5 different collections that will be used for the "moist run". The data (one zipped file per CT volume containing the DICOM slices) and locations of the nodules to be segmented (where available, in excel) are given below.