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Submission Requirements on Testing Datasets:

  1. Each submission should be a single compressed archive (zip) containing the segmentation results of all images. Segmentation files should be directly in the root of the archive, and not nested in a folder structure. Each segmentation should be a hdr/img file (e.g., subject-14-label.hdr and subject-14-label.img ) of type 8-bit unsigned char.
  2. The resolution, dimensions, and orientation of the segmentation results should be the same as the T1-weighted scans (voxel size: 0.8mm x 0.8mm x 0.8mm).
    Results should be named as subject-XX-label.hdr/img to subject-XX-label.hdr/img. Within these files the segmented tissues should be labeled as follows:
    0: Background (everything outside the cerebellum)
    1: Cerebrospinal fluid
    2: Gray matter
    3: White matter
  3. For each submission on testing datasets, a short description of the segmentation algorithm (1-2 pages) should be provided. Generally, maximal two submissions are allowed.
  4. Please consider the following guidelines for the content of the method description:
  • Is your algorithm automatic or semi-automatic? Describe the required user inputs, and the average time spent per scan, for semi-automatic algorithms.
  • List the overall structure of the algorithm in a step-wise fashion and describe each step of the algorithm in detail. Include pre- or post-processing steps, when required.
  • Is the algorithm trained with example data other than the training data provided by the cSeg-2022 challenge? If so, describe the characteristics of the training data.
  • If the algorithm has been tested on other datasets, you could consider including those results.
  • What is the average runtime of your algorithm, and on which system is this runtime achieved?

The following link is for uploading results on testing datasets only:

Upload Your Testing Results