11 citations · 19 across the 7 of their papers we have counts for
8 papers
Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence
Erik C. Johnson, Brian S. Robinson, Gautam K. Vallabha +17
Despite the progress in deep learning networks, efficient learning at the edge (enabling adaptable, low-complexity machine learning solutions) remains a critical need for defense a…
NeuroStorm: Accelerating Brain Science Discovery in the Cloud
Gregory Kiar, Robert J. Anderson, Alex Baden +24
Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales. However, our ability to capitalize on existing datasets, tools, and intellectual capa…
Neural Reconstruction Integrity: A metric for assessing the connectivity of reconstructed neural networks
Elizabeth P. Reilly, Jeffrey S. Garretson, William Gray Roncal +4
Neuroscientists are actively pursuing high-precision maps, or graphs, consisting of networks of neurons and connecting synapses in mammalian and non-mammalian brains. Such graphs,…
Science In the Cloud (SIC): A use case in MRI Connectomics
Gregory Kiar, Krzysztof J. Gorgolewski, Dean Kleissas +8
Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught…
SANTIAGO: Spine Association for Neuron Topology Improvement and Graph Optimization
William Gray Roncal, Colin Lea, Akira Baruah +1
Developing automated and semi-automated solutions for reconstructing wiring diagrams of the brain from electron micrographs is important for advancing the field of connectomics. Wh…
From sample to knowledge: Towards an integrated approach for neuroscience discovery
William Gray Roncal, Eva L Dyer, Doga Gürsoy +2
Imaging methods used in modern neuroscience experiments are quickly producing large amounts of data capable of providing increasing amounts of knowledge about neuroanatomy and func…
Gradient-Domain Fusion for Color Correction in Large EM Image Stacks
Michael Kazhdan, Kunal Lillaney, William Roncal +3
We propose a new gradient-domain technique for processing registered EM image stacks to remove inter-image discontinuities while preserving intra-image detail. To this end, we proc…
VESICLE: Volumetric Evaluation of Synaptic Interfaces using Computer vision at Large Scale
William Gray Roncal, Michael Pekala, Verena Kaynig-Fittkau +7
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 unders…