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.