EXACT: A collaboration toolset for algorithm-aided annotation of images with annotation version control
This tool addresses the problem of labor-intensive annotation tracking for researchers in fields like medical imaging and bioacoustics, though it is incremental as it builds on existing annotation and version control concepts.
The researchers tackled the challenge of managing collaborative image annotations by developing EXACT, an open-source platform that supports multi-gigapixel images and integrates a version control system, which has been successfully applied to diverse tasks such as cytology scoring and tumour annotation.
In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation. However, keeping track of these annotations to ensure a high-quality multi-purpose data set is a challenging and labour intensive task. We developed the open-source online platform EXACT (EXpert Algorithm Collaboration Tool) that enables the collaborative interdisciplinary analysis of images from different domains online and offline. EXACT supports multi-gigapixel medical whole slide images as well as image series with thousands of images. The software utilises a flexible plugin system that can be adapted to diverse applications such as counting mitotic figures with a screening mode, finding false annotations on a novel validation view, or using the latest deep learning image analysis technologies. This is combined with a version control system which makes it possible to keep track of changes in the data sets and, for example, to link the results of deep learning experiments to specific data set versions. EXACT is freely available and has already been successfully applied to a broad range of annotation tasks, including highly diverse applications like deep learning supported cytology scoring, interdisciplinary multi-centre whole slide image tumour annotation, and highly specialised whale sound spectroscopy clustering.