Omkar2118/datasets huggingface dataset:
BBBC005

Since robust foreground/background separation and segmentation of cellular objects (i.e.,identification of which pixels below to which objects) strongly depends on image quality, focus artifacts are detrimental to data quality. This image set provides examples of in- and out-of-focus synthetic images, which can be used for validation of focus metrics.

Image source: [https://bbbc.broadinstitute.org/BBBC005](https://bbbc.broadinstitute.org/BBBC005)
BBBC039

This image set is part of a high-throughput chemical screen on U2OS cells, with examples of 200 bioactive compounds. The effect of the treatments was originally imaged using the Cell Painting assay (fluorescence microscopy). This data set only includes the DNA channel of a single field of view per compound. These images present a variety of nuclear phenotypes, representative of high-throughput chemical perturbations. The main use of this data set is the study of segmentation algorithms that can separate individual nucleus instances in an accurate way, regardless of their shape and cell density. The collection has around 23,000 single nuclei manually annotated to establish a ground truth collection for segmentation evaluation.

This data set has a total of 200 fields of view of nuclei captured with fluorescence microscopy using the Hoechst stain. These images are a sample of the larger BBBC022 chemical screen. The images are stored as TIFF files with 520x696 pixels at 16 bits.

Source: [https://bbbc.broadinstitute.org/BBBC039](https://bbbc.broadinstitute.org/BBBC039)

Image source: [https://bbbc.broadinstitute.org/BBBC039](https://bbbc.broadinstitute.org/BBBC039)