Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

Events on April 12, 2021

Martin Styner, Director of the UNC Neuro Image Research and Analysis Laboratory and associate director of the Developmental Neuroimaging Core at the Carolina Institute for Developmental Disabilities Presents:

Imputation for longitudinal neuroimaging studies

April 12, 2021 at 12:00pm for 1hr


Title: Imputation for longitudinal neuroimaging studies

The infant brain undergoes a remarkable period of neural development that is crucial for the development of cognitive and behavioral capacities. Longitudinal magnetic resonance imaging (MRI) is able to both characterize the developmental trajectories as well as predict later outcome such as cognitive development or the emergence of disorders like ASD and ADHD. However, missing data at different time points is an unavoidable occurrence in longitudinal studies owing to participant attrition and scan failure. Compared to dropping incomplete data, data imputation is considered a better solution to address such missing data in order to preserve all available samples. Here I will present recent research of my lab in deep learning based data imputation in developmental neuroimaging studies, from simple approaches like auto encoders to more advanced ones like perceptive generative adversarial networks (GAN). Our results show that effective data imputation is possible, and that the significantly improved data size leads to enhanced outcome in regression and classification tasks. 

Posted by: Hong Xu