Image processing is one of the most important applications of recent machine learning (ML)
technologies. Convolutional neural networks (CNNs), a popular deep learning-based ML …

The field of connectomics aims to reconstruct the wiring diagram of Neurons and synapses
to enable new insights into the workings of the brain. Reconstructing and analyzing the …

Pixel-accurate tracking of objects is a key element in many computer vision applications,
often solved by iterated individual object tracking or instance segmentation followed by …

Neuron reconstruction algorithms used in electron microscope volumes have received
increasing attention in recent years. Most current methods are highly reliant on neuron …

Electron microscopy (EM) enables the reconstruction of neural circuits at the level of
individual synapses, which has been transformative for scientific discoveries. However, due …

Abstract Objects with complex structures pose significant challenges to existing instance
segmentation methods that rely on boundary or affinity maps, which are vulnerable to small …

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at
nanometer resolution. Dense reconstruction of cellular compartments in these EM volumes …

We show dense voxel embeddings learned via deep metric learning can be employed to
produce a highly accurate segmentation of neurons from 3D electron microscopy images. A …

The throughput of electron microscopes has increased significantly in recent years, enabling
detailed analysis of cell morphology and ultrastructure in fairly large tissue volumes …

Background Nanoscale connectomics, which aims to map the fine connections between
neurons with synaptic-level detail, has attracted increasing attention in recent years …