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Found 5 papers, 2 papers with code
Two Stream Active Query Suggestion for Active Learning in Connectomics
As a use case, we build an end-to-end active learning framework with our query suggestion method for 3D synapse detection and mitochondria segmentation in connectomics.
Direct Amortized Likelihood Ratio Estimation
Our estimator is simple to train and estimates the likelihood ratio using a single forward pass of the neural estimator.
AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions
Electron microscopy (EM) enables the reconstruction of neural circuits at the level of individual synapses, which has been transformative for scientific discoveries.
Biologically-Constrained Graphs for Global Connectomics Reconstruction
Most current state-of-the-art connectome reconstruction pipelines have two major steps: initial pixel-based segmentation with affinity prediction and watershed transform, and refined segmentation by merging over-segmented regions.
Ranked #1 on
Electron Microscopy Image Segmentation
on SNEMI3D
(Total Variation of Information metric)
Electron Microscopy Image Segmentation
graph construction
+2
Anisotropic EM Segmentation by 3D Affinity Learning and Agglomeration
The field of connectomics has recently produced neuron wiring diagrams from relatively large brain regions from multiple animals.
