Nipype: Opensource platform for unified and replicable interaction with existing neuroimaging tools

Satrajit Ghosh; Chris Burns; Dav Clark; Krzysztof J. Gorgolewski; Yaroslav Halchenko; Cindee Madison; Rosalia Tungaraza; Jarrod Millman

Nipype: Opensource platform for unified and replicable interaction with existing neuroimaging tools

Satrajit Ghosh, Chris Burns, Dav Clark, Krzysztof J. Gorgolewski, Yaroslav Halchenko, Cindee Madison, Rosalia Tungaraza, Jarrod Millman

Research output: Contribution to conference › Poster › peer-review

Abstract / Description of output

Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface. Nipype, an open-source, community-developed initiative under the umbrella of Nipy, is a Python project that solves these issues by providing a uniform interface to existing neuroimaging software and by facilitating interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., SPM, FSL), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.

Original language	English
Publication status	Published - 2010
Event	16th Annual Meeting of the Organization for Human Brain Mapping - Palau de Congressos de Catalunya, Barcelona, Spain Duration: 6 Jun 2010 → 10 Jun 2010

Conference

Conference	16th Annual Meeting of the Organization for Human Brain Mapping
Country/Territory	Spain
City	Barcelona
Period	6/06/10 → 10/06/10

Cite this

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title = "Nipype: Opensource platform for unified and replicable interaction with existing neuroimaging tools",

abstract = "Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface. Nipype, an open-source, community-developed initiative under the umbrella of Nipy, is a Python project that solves these issues by providing a uniform interface to existing neuroimaging software and by facilitating interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., SPM, FSL), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.",

author = "Satrajit Ghosh and Chris Burns and Dav Clark and Gorgolewski, {Krzysztof J.} and Yaroslav Halchenko and Cindee Madison and Rosalia Tungaraza and Jarrod Millman",

year = "2010",

language = "English",

note = "16th Annual Meeting of the Organization for Human Brain Mapping ; Conference date: 06-06-2010 Through 10-06-2010",

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TY - CONF

T1 - Nipype: Opensource platform for unified and replicable interaction with existing neuroimaging tools

AU - Ghosh, Satrajit

AU - Burns, Chris

AU - Clark, Dav

AU - Gorgolewski, Krzysztof J.

AU - Halchenko, Yaroslav

AU - Madison, Cindee

AU - Tungaraza, Rosalia

AU - Millman, Jarrod

PY - 2010

Y1 - 2010

N2 - Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface. Nipype, an open-source, community-developed initiative under the umbrella of Nipy, is a Python project that solves these issues by providing a uniform interface to existing neuroimaging software and by facilitating interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., SPM, FSL), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.

AB - Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface. Nipype, an open-source, community-developed initiative under the umbrella of Nipy, is a Python project that solves these issues by providing a uniform interface to existing neuroimaging software and by facilitating interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., SPM, FSL), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.

M3 - Poster

T2 - 16th Annual Meeting of the Organization for Human Brain Mapping

Y2 - 6 June 2010 through 10 June 2010

ER -

Nipype: Opensource platform for unified and replicable interaction with existing neuroimaging tools

Abstract / Description of output

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