236 citations · 433 across the 6 of their papers we have counts for
7 papers
Radiologist-level Performance by Using Deep Learning for Segmentation of Breast Cancers on MRI Scans
Lukas Hirsch, Yu Huang, Shaojun Luo +19
Purpose: To develop a deep network architecture that would achieve fully automated radiologist-level segmentation of cancers at breast MRI. Materials and Methods: In this retrospec…
Segmentation of MRI head anatomy using deep volumetric networks and multiple spatial priors
Lukas Hirsch, Yu Huang, Lucas C Parra
Purpose: Conventional automated segmentation of the head anatomy in MRI distinguishes different brain and non-brain tissues based on image intensities and prior tissue probability…
Finding influential nodes for integration in brain networks using optimal percolation theory
Gino Del Ferraro, Andrea Moreno, Byungjoon Min +7
Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficientl…
Multi-set Canonical Correlation Analysis simply explained
Lucas C Parra
There are a multitude of methods to perform multi-set correlated component analysis (MCCA), including some that require iterative solutions. The methods differ on the criterion the…
Correlated Components Analysis - Extracting Reliable Dimensions in Multivariate Data
Lucas C. Parra, Stefan Haufe, Jacek P. Dmochowski
How does one find dimensions in multivariate data that are reliably expressed across repetitions? For example, in a brain imaging study one may want to identify combinations of neu…
EEG in the classroom: Synchronised neural recordings during video presentation
Andreas Trier Poulsen, Simon Kamronn, Jacek Dmochowski +2
We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a…
Origins of power-law degree distribution in the heterogeneity of human activity in social networks
Lev Muchnik, Sen Pei, Lucas C. Parra +4
The probability distribution of number of ties of an individual in a social network follows a scale-free power-law. However, how this distribution arises has not been conclusively…