ONLINE CROSS-SECTIONAL AREA CALCULATION TOOL FOR THE SPINAL CORD


This is an automated tool based on the Spinal Cord Toolbox (SCT) for computing the cross-sectional area for each slice of a binarized segmentation of the spinal cord. The cross-sectional area is calculated by counting the pixels in each slice and then geometrically adjusting using centerline orientation.

Four output files will be generated:
  • angle_image.nii.gz: the cord segmentation where each slice's value is equal to the CSA (mm2)
  • csa_image.nii.gz: the cord segmentation where each slice's value is equal to the angle (in degrees) between the spinal cord centerline and the inferior-superior direction
  • csa_per_slice.txt: a CSV text file with z (first column), CSA in mm2 (second column) and angle with respect to the I-S direction in degrees (third column)
  • csa_per_slice.pickle: a pickle file with the same results as csa_per_slice.txt recorded in a DataFrame (panda structure) that can be reloaded afterwards


The results will be sent to the following e-mail address:


Select files (Maximum of 5 files with 100 Mb each in .nii or nii.gz formats):
[Select files - Binarized spinal cord segmentation image]
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 By filling in this form I agree to have the provided email address stored in order to use it as email address to send the requested results. I allow use of this email address for contacting me about the project. I understand that NiftyWeb will not disclose this information to any other parties.

Upload segmentation and calculate the cross-sectional area



The queue is empty and CSA is ready to process your files!
Total files processed so far: 6/6

Publications on CSA

We would appreciate it if the following references would be included in any published work that uses this resource:

  • Benjamin De Leener, Simon Lévy, Sara M. Dupont, Vladimir S. Fonov, Nikola Stikov, Louis Collins, Virginie Callot and Julien Cohen-Adad. SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. NeuroImage, Volume 145, Part A, January 2017, Pages 24-43
  • Ferran Prados, M. Jorge Cardoso, Ninon Burgos, Claudia AM Wheeler-Kingshott, Sebastien Ourselin. NiftyWeb: web based platform for image processing on the cloud. International Society for Magnetic Resonance in Medicine (ISMRM) 24th Scientific Meeting and Exhibition - Singapore 2016
  • http://niftyweb.cs.ucl.ac.uk/

DISCLAIMER: THIS ONLINE TOOL IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.