William R. Gray-Roncal, Ph.D.
William R. Gray-Roncal, Ph.D.
Johns Hopkins University Applied Physics Laboratory
Verified email at jhu.edu
Title
Cited by
Cited by
Year
Saturated reconstruction of a volume of neocortex
N Kasthuri, KJ Hayworth, DR Berger, RL Schalek, JA Conchello, ...
Cell 162 (3), 648-661, 2015
7622015
Graph classification using signal-subgraphs: Applications in statistical connectomics
JT Vogelstein, WG Roncal, RJ Vogelstein, CE Priebe
IEEE transactions on pattern analysis and machine intelligence 35 (7), 1539-1551, 2012
752012
Quantifying mesoscale neuroanatomy using X-ray microtomography
EL Dyer, WG Roncal, JA Prasad, HL Fernandes, D Gürsoy, V De Andrade, ...
Eneuro 4 (5), 2017
642017
The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience
R Burns, W Gray Roncal, D Kleissas, K Lillaney, P Manavalan, E Perlman, ...
arXiv preprint arXiv:1306.3543, 2013
592013
Magnetic resonance connectome automated pipeline: an overview
WR Gray, JA Bogovic, JT Vogelstein, BA Landman, JL Prince, ...
IEEE pulse 3 (2), 42-48, 2012
542012
MIGRAINE: MRI graph reliability analysis and inference for connectomics
WG Roncal, ZH Koterba, D Mhembere, DM Kleissas, JT Vogelstein, ...
2013 IEEE Global Conference on Signal and Information Processing, 313-316, 2013
47*2013
A community-developed open-source computational ecosystem for big neuro data
JT Vogelstein, E Perlman, B Falk, A Baden, WG Roncal, ...
Nature methods 15 (11), 846-847, 2018
342018
Science in the cloud (SIC): A use case in MRI connectomics
G Kiar, KJ Gorgolewski, D Kleissas, WG Roncal, B Litt, B Wandell, ...
Giga Science 6 (5), gix013, 2017
342017
Vesicle: volumetric evaluation of synaptic interfaces using computer vision at large scale
WG Roncal, M Pekala, V Kaynig-Fittkau, DM Kleissas, JT Vogelstein, ...
arXiv preprint arXiv:1403.3724, 2014
34*2014
An automated images-to-graphs framework for high resolution connectomics
WR Gray Roncal, DM Kleissas, JT Vogelstein, P Manavalan, K Lillaney, ...
Frontiers in neuroinformatics 9, 20, 2015
302015
A high-throughput pipeline identifies robust connectomes but troublesome variability
G Kiar, EW Bridgeford, WRG Roncal, V Chandrashekhar, D Mhembere, ...
bioRxiv, 188706, 2018
27*2018
Computing Scalable Multivariate Glocal Invariants of Large (Brain-) Graphs
D Mhembere, W Gray Roncal, D Sussman, CE Priebe, R Jung, S Ryman, ...
IEEE GlobalSIP, 2013
242013
ndmg: Neurodata’s mri graphs pipeline
G Kiar, W Gray Roncal, D Mhembere, E Bridgeford, R Burns, J Vogelstein
Zenodo, 2016
162016
Eliminating accidental deviations to minimize generalization error and maximize replicability: applications in connectomics and genomics
EW Bridgeford, S Wang, Z Yang, Z Wang, T Xu, C Craddock, J Dey, G Kiar, ...
BioRxiv, 802629, 2021
112021
The block object storage service (bossDB): A cloud-native approach for petascale neuroscience discovery
R Hider, DM Kleissas, D Pryor, T Gion, L Rodriguez, J Matelsky, ...
bioRxiv, 217745, 2019
112019
Neural reconstruction integrity: A metric for assessing the connectivity accuracy of reconstructed neural networks
EP Reilly, JS Garretson, WR Gray Roncal, DM Kleissas, BA Wester, ...
Frontiers in neuroinformatics 12, 74, 2018
112018
Mine your own view: Self-supervised learning through across-sample prediction
M Azabou, MG Azar, R Liu, CH Lin, EC Johnson, K Bhaskaran-Nair, ...
arXiv preprint arXiv:2102.10106, 2021
102021
A three-dimensional thalamocortical dataset for characterizing brain heterogeneity
JA Prasad, AH Balwani, EC Johnson, JD Miano, V Sampathkumar, ...
Scientific Data 7 (1), 1-7, 2020
92020
Big data reproducibility: Applications in brain imaging and genomics
EW Bridgeford, S Wang, Z Yang, Z Wang, T Xu, C Craddock, J Dey, G Kiar, ...
bioRxiv, 802629, 2020
72020
Toward a reproducible, scalable framework for processing large neuroimaging datasets
EC Johnson, M Wilt, LM Rodriguez, R Norman-Tenazas, C Rivera, ...
BioRxiv, 615161, 2019
72019
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