BioImage Archive AI datasetsalpha

A selection of AI related studies

This is a collection of AI/Machine Learning datasets from the BioImage Archive from which one or more images have been converted to OME-Zarr. It is intended to present the AI related datasets with relevant tags and visualisation of images from the archive's collection, and to provide easy access to AI datasets and encourage tool development.

S-BIAD531

A machine learning-based classifier trained to detect temporal developmental differences across groups of zebrafish embryos, using images from a standard live imaging widefield microscope.


1142 images , 1062 annotations

Tags: time series, object classification, training data, pixel classification, test data, segmentation, Time series

S-BIAD599

Automated single-cell segmentation and point cloud-based morphometry of 3D zebrafish embryo images


584 images , 196 annotations

Tags: instance segmentation, 3D

S-BIAD463

Automated detection and classification of high endothelial venules (HEVs) in tumor-draining lymph nodes using deep learning


1285 images

Tags: object classification, training data, pixel segmentation

S-BIAD634

Ground-truth annotated fluorescence image dataset for training nuclear segmentation methods


388 images , 388 annotations

Tags: test data, ground truth annotations, training data, instance segmentation

S-BIAD686

Ultrasound images of mouse embryos


693 images , 451 annotations

Tags: test data, ground truth annotations, training data

S-BIAD493

Multi-channel images and ground truth annotations of Myelin used to develop an automated Myelin annotating Machine Learning tool


25 images , 5 annotations

Tags: ground truth, training data

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