Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets
Fig 21
Segmentation quality metric [52] applied to outputs from 5 segmentation pipelines and types of errors displayed as a color map (on a common Z slice). The green cell regions represent regions of complete overlap between ground truth and predicted segmentations (i.e., regions of fully correct segmentation). Red regions represent over and blue regions represent undersegmentation errors. White regions are regions where cells were mistaken for background. The benefit of this metric is that it helps to estimate the rate of over- and undersegmentations as a volumetric statistics and as spatial distributions.