An annotated high-content fluorescence microscopy dataset with Hoechst 33342-stained nuclei and manually labelled outlines.

ABSTRACT: Automated detection of cell nuclei in fluorescence microscopy images is a key task in bioimage analysis. It is essential for most types of microscopy-based high-throughput drug and genomic screening and is often required in smaller scale experiments as well. To develop and evaluate algorithms and neural networks that perform instance or semantic segmentation for detecting nuclei, high quality annotated data is essential. Here we present a benchmarking dataset of fluorescence microscopy images with Hoechst 33342-stained nuclei together with annotations of nuclei, nuclear fragments and micronuclei. Images were randomly selected from an RNA interference screen with a modified U2OS osteosarcoma cell line, acquired on a Thermo Fischer CX7 high-content imaging system at 20x magnification. Labell

SUBMITTER: Arvidsson M 

PROVIDER: S-EPMC9727632 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature