Extended Data Fig. 5: Performance of ACE in brain-wide segmentation of neuronal cell bodies in unseen dataset 2. | Nature Methods

Extended Data Fig. 5: Performance of ACE in brain-wide segmentation of neuronal cell bodies in unseen dataset 2.

From: A deep learning pipeline for three-dimensional brain-wide mapping of local neuronal ensembles in teravoxel light-sheet microscopy

Extended Data Fig. 5

a. An axial view from a random depth of whole-brain c-Fos expression with an enlarged view of a cortical patch plus its associated ground truth data in red (b). c. The segmentation maps (blue) predicted by the ACE UNETR ensemble for the enlarged subregion are shown and compared with the Ilastik output for the same patch (blue). d and e. Quantitative evaluation of the segmentation accuracy of ACE vs. Ilastik (d) and detection accuracy of ACE vs. Cellfinder (e) in terms of average Dice coefficient, precision, recall, 95% Hausdorff distance, and F1 score on (N: 152 unique patches of 963≃0.17×0.17×0.38 \({{mm}}^{3}\)). Box plots: box limits, upper and lower quartiles; center line, median; whiskers, 1.5× interquartile range; points, outliers. Mann-Whitney U test (two-sided), ***p < 0.0001.

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