Algorithm #2: sct_deepseg_scΒΆ

As its name suggests, sct_deepseg_sc is based on deep learning. It is a newer algorithm, having been introduced to SCT in 2018. The steps of the algorithm are as follows:

1. Spinal cord detection:

First, a convolutional neural network is used to generate a probablistic heatmap for the location of the spinal cord.

2. Centerline detection:

The heatmap is then fed into the OptiC algorithm to detect the spinal cord centerline.

3. Patch extraction:

The spinal cord centerline is used to extract a patch from the image. (This is done to exclude regions that we are certain do not contain the spinal cord.)

4. Segmentation:

Lastly, a second convolutional neural network is applied to the extracted patch to segment the spinal cord.

https://raw.githubusercontent.com/spinalcordtoolbox/doc-figures/master/spinalcord-segmentation/sct_deepseg_sc_steps.png