Sarc-Graph: Automated segmentation, tracking, and analysis of sarcomeres in hiPSC-derived cardiomyocytes
Fig 5
For each image, the number of sarcomeres successfully segmented and tracked (out of 20 possible) is reported.
Running the algorithm on synthetic data shows that the code is robust to geometry and noise up to a limit: (a) Illustration of successful z-disc and sarcomere segmentation and tracking for a curved geometry in the presence of noise; (b) Performance degrades when the baseline geometry moves partially out of plane (here slanted in the z-direction), and when the sarcomere chain is too distorted (here high amplitude to period ratio for sinusoidal geometry); (c) Performance degrades in the presence of Perlin noise, in particular noise that is similar in size and brightness to the z-discs themselves.