The brain atlas, which provides information about the distribution of genes, proteins,
neurons, or anatomical regions in the brain, plays a crucial role in contemporary …

Segmenting individual neurons from a large number of noisy raw images is the first step in
building a comprehensive map of neuron-to-neuron connections for predicting information …

We present PyTorch Connectomics (PyTC), an open-source deep-learning framework for
the semantic and instance segmentation of volumetric microscopy images, built upon …

Recent studies in neuroscience have shown the great promise of an approach known as
connectomics, which seeks to map the brain by the connections between neurons. Attempts …

Imaging the expression patterns of reporter constructs is a powerful tool to dissect the
neuronal circuits of perception and behavior in the adult brain of Drosophila, one of the …

Reconstructing the intricate local morphology of neurons as well as their long-range
projecting axons can address many connectivity related questions in neuroscience. While …

To investigate the anatomical organization of neural circuits across the whole brain, it is
essential to register the experimental brain tissues to a reference atlas accurately. This …

A fundamental challenge in machine learning-based segmentation of large-scale brain
microscopy images is the time and domain expertise required by humans to generate …

Segmenting individual neurons in multi-neuron light microscopy (LM) recordings is intricate
due to the long, thin filamentous and widely branching morphology of individual neurons …

Recent studies have demonstrated the superiority of deep learning in medical image
analysis, especially in cell instance segmentation, a fundamental step for many biological …