6 citations · 11 across the 4 of their papers we have counts for
8 papers
DeepDefacer: Automatic Removal of Facial Features via U-Net Image Segmentation
Anish Khazane, Julien Hoachuck, Krzysztof J. Gorgolewski +1
Recent advancements in the field of magnetic resonance imaging (MRI) have enabled large-scale collaboration among clinicians and researchers for neuroimaging tasks. However, resear…
NEMAR: An open access data, tools, and compute resource operating on NeuroElectroMagnetic data
Arnaud Delorme, Dung Truong, Choonhan Youn +5
To take advantage of recent and ongoing advances in large-scale computational methods, and to preserve the scientific data created by publicly funded research projects, data archiv…
Challenges for cognitive decoding using deep learning methods
Armin W. Thomas, Christopher Ré, Russell A. Poldrack
In cognitive decoding, researchers aim to characterize a brain region's representations by identifying the cognitive states (e.g., accepting/rejecting a gamble) that can be identif…
NeuroQuery: comprehensive meta-analysis of human brain mapping
Jérôme Dockès, Russell Poldrack, Romain Primet +5
Reaching a global view of brain organization requires assembling evidence on widely different mental processes and mechanisms. The variety of human neuroscience concepts and termin…
Computational and informatics advances for reproducible data analysis in neuroimaging
Russell A. Poldrack, Krzysztof J. Gorgolewski, Gael Varoquaux
The reproducibility of scientific research has become a point of critical concern. We argue that openness and transparency are critical for reproducibility, and we outline an ecosy…
Text to brain: predicting the spatial distribution of neuroimaging observations from text reports
Jérôme Dockès, Demian Wassermann, Russell Poldrack +3
Despite the digital nature of magnetic resonance imaging, the resulting observations are most frequently reported and stored in text documents. There is a trove of information unta…