Evaluation of cell segmentation methods without reference segmentations

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Abstract
We developed metrics and an open source tool to evaluate the cell segmentation quality of multichannel images without a human-labeled reference. Deep learning–based methods performed the best, but postprocessing to ensure proper matching of cell and nuclear masks dramatically improved performance.
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