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Identifying spinal cord regeneration

Photo credit to Vaun0815

Segmentation of spinal cord images

More fun and useful image-processing tricks in Python.

[Caption] Cross-sectional images of a mouse's spinal cord. The mice in these experiments suffer a hemisection spinal cord injury. Next dyes are applied in the brain which travel down working nerves. When the mice are sacrificed weeks later, the dye is visible in the spinal cross-sections in areas where the nerves have regenerated. [Upper left] Original image shown in log scale. [Upper right] Fiber identification obtained by Otsu thresholding of raw (not log) image. The code found 23.8% of the nerve fibers on the left side of the image and 76.1% on the right. [Lower left] spinal cord boundary identified by Otsu thresholding of the log image. Midline defined as vertical line with least contact with spinal cord in the middle half of the image. [Lower right] Heat map obtained by convolution of nerve fibers ids with 50 pixel square matrix of 1s. Displayed in log scale for clarity.

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