Unbiased image segmentation assessment toolkit for quantitative differentiation of state-of-the-art algorithms and pipelines.

ABSTRACT:

Background

Image segmentation pipelines are commonly used in microscopy to identify cellular compartments like nucleus and cytoplasm, but there are few standards for comparing segmentation accuracy across pipelines. The process of selecting a segmentation assessment pipeline can seem daunting to researchers due to the number and variety of metrics available for evaluating segmentation quality.

Results

Here we present automated pipelines to obtain a comprehensive set of 69 metrics to evaluate segmented data and propose a selection methodology for models based on quantitative analysis, dimension reduction or unsupervised classification techniques and informed selection criteria.

Conclusion

We show that the metrics used here can often be reduced to a small number of metr

SUBMITTER: Goyal V 

PROVIDER: S-EPMC10568754 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature