HistokatFusion

Correlating Histopathology

Large-Scale Image Fusion in Digital Pathology

HistokatFusion combines the information from multiple images in histopathology using image registration. The technology has been used in biomarker research, AI development and to combine and evaluate different stains.

Features

Award-winning performance

Nucleus-accurate

The algorithm behind HistokatFusion won the first place at the ANHIR challenge on histological image registation.

Robust in routine use

Automatic initial alignment of slide images. Most bright-field images do not require manual interactions.

Extremely fast

CPU < 10s
GPU < 1s
for an accurate alignment of two consecutive sections

Projects using HistokatFusion

Automatic Annotations using Image Registration

Wouter Bulten et al., Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard. Nature Scientific Reports, 2019

https://doi.org/10.1038/s41598-018-37257-4

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Tumor Inflitrating Lymphocytes in Breast Cancer

Maschenka CA Balkenhol et al., Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics, The Breast, 2021

https://doi.org/10.1016/j.breast.2021.02.007

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Virtual Staining

C. Mercan et al., Virtual Staining for Mitosis Detection in Breast Histopathology, IEEE 17th International Symposium on Biomedical Imaging (ISBI), 2020

https://doi.org/10.1109/ISBI45749.2020.9098409

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Publications on HistokatFusion

Accuracy of Re-stained and Consecutive Section Registration

J. Lotz, N. Weiss, J. vd Laak, S. Heldmann, High-resolution Image Registration of Consecutive and Re-stained Sections in Histopathology. submitted, arxiv preprint, 2021

https://arxiv.org/abs/2106.13150

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HistokatFusion wins 1st place at ANHIR challenge

J. Borovec et al., ANHIR: Automatic Non-Rigid Histological Image Registration Challenge, IEEE Transactions on Medical Imaging, 2020

https://doi.org/10.1109/TMI.2020.2986331

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Patch-Based Image Registration

J. Lotz, Combined Local and Global Image Registration and its Application to Large-Scale Images in Digital Pathology, Dissertation, University of Lübeck, 2020

http://dx.doi.org/10.24406/mevis-n-638730

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