Volume EM data challenges

WEBKNOSSOS

Learn from leading experts as they share practical solutions for handling massive Volume EM datasets and improving collaborative workflows.

<h3>Solving Volume EM Data Challenges: An Online Symposium</h3>Join us on Thursday, March 6, 2025, at 5:00 PM CET for a focused two-hour symposium addressing the critical challenges in Volume Electron Microscopy (vEM). This free online event features four expert-led talks, each followed by a live Q&amp;A, providing insights into solutions for scaling massive datasets, improving segmentation accuracy, streamlining collaborative workflows, and managing complex data efficiently.This symposium is ideal for researchers, life scientists, imaging facilities, and anyone navigating the complexities of vEM. Gain actionable insights and connect with leading experts shaping the future of the field.Admission is free, but registration is required to secure your spot and receive event reminders.Reserve your spot today and join the conversation!

Agenda

Serial electron microscopy is revolutionizing our understanding of retinal synaptic circuits - the hardware of computation in early vision. This can now all be done much faster, more flexibly, more collaboratively and at lower cost than ever before.

I will talk about what drew me into connectomic analysis and how it has paid off. I’ll discuss the different modes of analysis - from targeted single-cell studies to large-scale reconstructions - and how our team has tackled connectivity analysis across large retinal volumes (~250 × 250 µm). I will highlight key insights from several mouse retina datasets, explore the intersection of connectomics with functional and molecular approaches, and discuss efforts to develop public platforms for community-based proofreading and data sharing - an area where WEBKNOSSOS is already helping to provide the necessary infrastructure.

Strategies & technologies for large-scale segmentation in retinal connectomics

A mechanistic understanding of how neuronal circuits work can be achieved by integrating insights of physiology and structure at neuronal circuit scale. However, two major challenges arise: First, both insights can rarely be gathered from a single imaging modality, requiring correlative approaches to combine compatible techniques. Second, beyond six orders of magnitude separate the necessary detail (membranes, synapses) from the minimal landscape (complete neuronal circuits), making the necessary maps data heavy. Robust data management infrastructure is essential to store, analyse, and share the multiple datasets involved. We have studied how neurons in the glomerular columns in the mouse olfactory bulb respond to odours given their connectivity, by combining in vivo 2-photon microscopy with synchrotron X-ray holographic nanotomography. I will discuss how this neuronal circuit computes information, and how this approach can be used to answer multimodal questions in biological tissues.

Mapping the neuronal circuits for smell with light and X-rays

The field of volume electron microscopy (vEM) has been revolutionized by connectomic approaches in brain, but its potential for peripheral tissues remains largely untapped. Our lab is pioneering vEM workflows for liver and other peripheral tissues, enabling quantitative connectomic analyses and 3D-tissue reconstruction of large datasets generated across multiple European sites (Spain, Sweden, and the UK). Without onsite SEM access, we have specialized in tissue array design and creative workflows for data acquisition, annotation, and sharing. Despite being a small lab, we tackle the challenge of managing and analyzing increasingly large datasets with a focus on organization and collaboration. Annotation is central to our work, linking skeletonized and segmented 3D features directly to interactive spreadsheets for seamless integration of measurements. This talk highlights our journey in adapting vEM workflows to peripheral tissues, showing the power of thinking "outside the brain box".

Thinking outside the (brain) box: vEM workflows in Liver

Volume EM datasets are growing in size and complexity, pushing the limits of traditional analysis workflows. How can researchers efficiently handle terabytes of data, streamline collaboration, and leverage machine learning for faster insights?

WEBKNOSSOS is a fully web-based platform optimized for large-scale EM. With no installation required, researchers can instantly access, organize, and analyze their data from anywhere. Advanced tools enable fast, collaborative annotations, detailed segment statistics, and automated rendering.

New AI-powered features now make vEM workflows even more efficient: integrated ML-based image alignment, automated neuron segmentation in just a few clicks, and the ability to train custom models directly within WEBKNOSSOS. This talk will showcase how these innovations are transforming data analysis, making connectomics and ultrastructural studies more scalable, accessible, and reproducible than ever before.

Comprehensive solutions for vEM data challenges

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Volume EM data challenges

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