Sarc-Graph: Automated segmentation, tracking, and analysis of sarcomeres in hiPSC-derived cardiomyocytes
Fig 3
Segmenting and tracking the z-discs and sarcomeres: (a) An example of a raw synthetic two-dimensional (2D) input image; (b) The Laplacian of the input image is used to detect the high gradients present at the edge of every z-disc [27]; (c) z-discs are identified as closed contours where the value of the Laplacian exceeds the threshold computed with Otsu’s method [28]; (d) Sarcomeres are procedurally identified from the segmented z-discs; (e) Sarcomeres and z-discs are tracked independently between frames with the Python trackpy package [29]; (f) The algorithm to segment sarcomeres is based on linking the approximately parallel z-discs to their closest neighbors in the direction perpendicular to the z-disc; (g) Sarcomere properties are computed from the pair of associated z-discs; (h) Tracking each sarcomere leads to multiple spatially resolved time series.