Description
PyData SF 2016
The Nipype project unifies the way hundreds of brain imaging tools can be run and also provides means to quickly prototype image analysis pipelines as well as deploy them at scale both at high performance clusters as well as the cloud. Nipype is being used in labs, hospitals and SaaS companies around the world and has a strong open source community of developers.
Human brain imaging has seen an enormous growth in terms of data analysis methods in the past 25 years. However, many of those methods are implemented in a plethora of different labs using heterogenous tools, languages, and data management standards. The Neuroimaging in Python (Nipy) community provides an ecosystem of scientific tools that build on the PyData stack. The Nipype project unifies the way hundreds of brain imaging tools can be run and also provides means to quickly prototype image analysis pipelines as well as deploy them at scale both at high performance clusters as well as the cloud. Nipype is being used in labs, hospitals and SaaS companies around the world and has a strong open source community of developers.