FIGURE

Figure S1.

ID

ZDB-FIG-250523-62

Publication

Yang et al., 2025 - Deep learning models link local cellular features with whole-animal growth dynamics in zebrafish

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Figure S1.

U-Net facilitates the automatic quantification of fish trunk surface area.

(A) Schematic illustration of the local palmskin images used for machine learning. Two 465 × 465 μm images were captured from each individual, centered on the anal protrusion: the anterior (A) and posterior (P) regions. Scale bar, 50 μm. (B) Schematic flowchart of the input, U-Net automated segmentation training, and growth size output. (C) Representative bright-field images of small- and large-sized fish and corresponding U-Net generated segmentations. Scale bar, 1 mm. SL, standard length. TSA, trunk surface area. (D) Fish growth states were examined in terms of standard length and trunk surface area. Each blue dot represents one larva, with a total of 361 larvae shown.

Expression Data

Expression Detail

Antibody Labeling

Phenotype Data

Phenotype Detail

Acknowledgments

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