Figure 6.

Pipeline for spatiotemporal quantification of calcium signatures. (A) Automatic segmentation of pouch region with deep-learning segmentation algorithm was developed for this study. Outlines represent the pouch at the initial time point (white) and the final time point (yellow). (B) Registration of raw images onto canonical pouch shapes is shown. (C) Extraction of amplitudes (Amp), frequency (F), and integrated intensity (Int) from Ca²⁺ traces for individual region of interest (ROI) was performed. (D) The Ca²⁺ signature is computed for each spatial position within each pouch to generate a spatial map. (E) Each spatial map is transformed onto a canonical coordinate system to align the anterior-posterior and dorsal-ventral axes. (F) Each set of transformed spatial maps is averaged at each position to generate a composite spatial map. The cross indicates the orientation of the wing disc. Scale bars, 100 μm. To see this figure in color, go online.