# EXACT: A collaboration toolset for algorithm-aided annotation of images with annotation version control

arXiv: https://arxiv.org/abs/2004.14595 · HTML: https://mlsanity.com/paper/2004.14595/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Apr 2020.

## Built on by (most cited first, 16 of 16)

- [Mitosis domain generalization in histopathology images -- The MIDOG challenge](https://mlsanity.com/paper/2204.03742/) (2022)
- [Domain generalization across tumor types, laboratories, and species -- insights from the 2022 edition of the Mitosis Domain Generalization Challenge](https://mlsanity.com/paper/2309.15589/) (2023)
- [Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset](https://mlsanity.com/paper/2201.11446/) (2022)
- [An unobtrusive quality supervision approach for medical image annotation](https://mlsanity.com/paper/2211.06146/) (2022)
- [Improved HER2 Tumor Segmentation with Subtype Balancing using Deep Generative Networks](https://mlsanity.com/paper/2211.06150/) (2022)
- [Superpixel Pre-Segmentation of HER2 Slides for Efficient Annotation](https://mlsanity.com/paper/2201.07572/) (2022)
- [End-to-end Learning for Image-based Detection of Molecular Alterations in Digital Pathology](https://mlsanity.com/paper/2207.00095/) (2022)
- [Is Medieval Distant Viewing Possible? : Extending and Enriching Annotation of Legacy Image Collections using Visual Analytics](https://mlsanity.com/paper/2208.09657/) (2022)
- [On the Value of PHH3 for Mitotic Figure Detection on H&E-stained Images](https://mlsanity.com/paper/2406.19899/) (2024)
- [Generalist Segmentation Algorithm for Photoreceptors Analysis in Adaptive Optics Imaging](https://mlsanity.com/paper/2408.14810/) (2024)
- [Inter-Species Cell Detection: Datasets on pulmonary hemosiderophages in equine, human and feline specimens](https://mlsanity.com/paper/2108.08529/) (2021)
- [First steps on Gamification of Lung Fluid Cells Annotations in the Flower Domain](https://mlsanity.com/paper/2111.03663/) (2021)
- [Nuclear Pleomorphism in Canine Cutaneous Mast Cell Tumors: Comparison of Reproducibility and Prognostic Relevance between Estimates, Manual Morphometry and Algorithmic Morphometry](https://mlsanity.com/paper/2309.15031/) (2023)
- [A bag of tricks for real-time Mitotic Figure detection](https://mlsanity.com/paper/2508.19804/) (2025)
- [Dataset creation for supervised deep learning-based analysis of microscopic images -- review of important considerations and recommendations](https://mlsanity.com/paper/2512.04564/) (2025)
- [Safety-oriented sidewalk and road segmentation for smartphone-based assistive navigation](https://mlsanity.com/paper/2607.21137/) (2026)

## Abstract (arXiv)

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.