Medical sciences have benefited from emerging open source web services and virtual technologies in recent years. These tools provide a common virtual platform for data collection, processing pipelines, and cross validation of research outcomes. Using these virtual services facilitates collaboration among remote sites and allows separate teams to reproduce study findings. Several large blueprint NIH grants followed this trend and opened their brain databases as well as their image processing pipelines, which enabled researchers with different backgrounds to test their clinical hypotheses more easily and collaboratively. However, many researchers are using common datasets and processing pipelines, assessing quality of the processed data and manual correction of the failures are existing challenges for those researchers. Several neurologists or radiologists are required to go through thousands of images, overlay processed data, browse each patient’s data, and manipulate the data to prepare them for their specific
studies. It is a tedious and time-consuming task, which can take up to a year for a study with a medium sample size. This creates a major bottleneck in the experimental process. Remote access to processed data is a challenge due to large file sizes, lack of software support, and data protection policies. To address these challenges, we have developed a collaborative web service for quality control as well as virtual reality (VR) software for manual manipulation of neuroanatomical magnetic responance imaging (MRI) data. 

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