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Found 7 papers, 0 papers with code
A Community-Developed Open-Source Computational Ecosystem for Big Neuro Data
Big imaging data is becoming more prominent in brain sciences across spatiotemporal scales and phylogenies.
Neurons and Cognition Quantitative Methods
SANTIAGO: Spine Association for Neuron Topology Improvement and Graph Optimization
Our automated approach improves the local subgraph score by more than four times and the full graph score by 60 percent.
Quantifying mesoscale neuroanatomy using X-ray microtomography
Methods for resolving the 3D microstructure of the brain typically start by thinly slicing and staining the brain, and then imaging each individual section with visible light photons or electrons.
An Automated Images-to-Graphs Framework for High Resolution Connectomics
Finally, we deploy a reference end-to-end version of the pipeline on a large, publicly available data set.
Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes
The contribution of this work is the introduction of a straightforward and robust pipeline which annotates axoplasmic reticula with high precision, contributing towards advancements in automatic feature annotations in neural EM data.
Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes using High-Resolution Neural EM Data
Accurately estimating the wiring diagram of a brain, known as a connectome, at an ultrastructure level is an open research problem.
VESICLE: Volumetric Evaluation of Synaptic Interfaces using Computer vision at Large Scale
An open challenge problem at the forefront of modern neuroscience is to obtain a comprehensive mapping of the neural pathways that underlie human brain function; an enhanced understanding of the wiring diagram of the brain promises to lead to new breakthroughs in diagnosing and treating neurological disorders.
