FIGURE

Figure 3—figure supplement 2.

ID

ZDB-FIG-200523-10

Publication

Hailstone et al., 2020 - CytoCensus, mapping cell identity and division in tissues and organs using machine learning

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Figure 3—figure supplement 2.

Comparison of CytoCensus performance.

Related to Figure 3. (A’ A’) The F1-score (see Supplemental Information) was plotted for different levels of training from annotation of a single NB cell, up to annotations of 21 individual NBs. As training examples are added, results improve but rapidly approach maximum with little training (A′′) F1-score for varying sizes of sigma (radius of cell detection in pixels). Performance is optimal at sigma = 10, which is slightly smaller than the radius of a NB. (B′) Cell Segmentation Benchmark overall performance (mean of Detection and Segmentation scores) (B′′) Cell Segmentation Benchmark Detection performance (B′′′) Cell Segmentation Benchmark Segmentation performance. Colours indicate ranking (red = worst, green = best).

Expression Data

Expression Detail

Antibody Labeling

Phenotype Data

Phenotype Detail

Acknowledgments

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