Annotation techniques for large-scale volume EM datasets

Generating annotations from volumetric electron microscopic (EM) image datasets is important for the work of many neuroscientists. As these EM datasets massively grow in size to many terabytes, smart tools as well as collaboration workflows are required to obtain high-quality annotations. The resulting annotations can be directly used for visualization or quantification purposes or indirectly, by training or evaluating a Machine Learning (ML) system...

New annotation and usability features in webKnossos

Today I would like to give you an overview of the many new features and UX improvements that we added to webKnossos over the last half-year.

At scalable minds, webKnossos is our primary tool for viewing the results of our automated neuron reconstructions, collaborate on training data annotation, and share the results with colleagues. Many of the new features are therefore inspired by our work in Connectomics and biomedical image reconstruction...

Cross-Dataset Segmentation Models

At scalable minds we work a lot with research labs in the Connectomics field and beyond to help them with automated image analysis and EM dataset reconstructions. We use state-of-the-art machine learning algorithms for automated dense reconstructions of neuron connections in brain tissue. Our alignment and segmentation tools are optimized to handle the terabyte-scale 3D EM datasets...