Pydpiper: A Flexible Toolkit for Constructing Novel Registration Pipelines
Using neuroimaging technologies to elucidate the relationship between genotype and phenotype and brain and behavior will be a key contribution to biomedical research in the twenty-first century. Among the many methods for analyzing neuroimaging data, image registration deserves particular attention...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2014-07-01
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| Series: | Frontiers in Neuroinformatics |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00067/full |
| _version_ | 1819209137241718784 |
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| author | Miriam eFriedel Matthijs C van Eede Jon ePipitone M Mallar Chakravarty M Mallar Chakravarty M Mallar Chakravarty Jason P Lerch Jason P Lerch |
| author_facet | Miriam eFriedel Matthijs C van Eede Jon ePipitone M Mallar Chakravarty M Mallar Chakravarty M Mallar Chakravarty Jason P Lerch Jason P Lerch |
| author_sort | Miriam eFriedel |
| collection | DOAJ |
| description | Using neuroimaging technologies to elucidate the relationship between genotype and phenotype and brain and behavior will be a key contribution to biomedical research in the twenty-first century. Among the many methods for analyzing neuroimaging data, image registration deserves particular attention due to its wide range of applications. Finding strategies to register together many images and analyze the differences between them can be a challenge, particularly given that different experimental designs require different registration strategies. Moreover, writing software that can handle different types of image registration pipelines in a flexible, reusable and extensible way can be challenging. In response to this challenge, we have created Pydpiper, a neuroimaging registration toolkit written in Python. Pydpiper is an open-source, freely available pipeline framework that provides multiple modules for various image registration applications. Pydpiper offers five key innovations. Specifically: (1) a robust file handling class that allows access to outputs from all stages of registration at any point in the pipeline; (2) the ability of the framework to eliminate duplicate stages; (3) reusable, easy to subclass modules; (4) a development toolkit written for non-developers; (5) four complete applications that run complex image registration pipelines ``out-of-the-box.'' In this paper, we will discuss both the general Pydpiper framework and the various ways in which component modules can be pieced together to easily create new registration pipelines. This will include a discussion of the core principles motivating code development and a comparison of Pydpiper with other available toolkits. We also provide a comprehensive, line-by-line example to orient users with limited programming knowledge and highlight some of the most useful features of Pydpiper. In addition, we will present the four current applications of the code. |
| first_indexed | 2024-12-23T05:50:30Z |
| format | Article |
| id | doaj.art-c4870d720fe34d328e72aef028f7250e |
| institution | Directory Open Access Journal |
| issn | 1662-5196 |
| language | English |
| last_indexed | 2024-12-23T05:50:30Z |
| publishDate | 2014-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj.art-c4870d720fe34d328e72aef028f7250e2022-12-21T17:57:58ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962014-07-01810.3389/fninf.2014.0006779170Pydpiper: A Flexible Toolkit for Constructing Novel Registration PipelinesMiriam eFriedel0Matthijs C van Eede1Jon ePipitone2M Mallar Chakravarty3M Mallar Chakravarty4M Mallar Chakravarty5Jason P Lerch6Jason P Lerch7Hospital for Sick ChildrenHospital for Sick ChildrenCentre for Addiction and Mental HealthCentre for Addiction and Mental HealthUniversity of TorontoRotman Research InstituteHospital for Sick ChildrenUniversity of TorontoUsing neuroimaging technologies to elucidate the relationship between genotype and phenotype and brain and behavior will be a key contribution to biomedical research in the twenty-first century. Among the many methods for analyzing neuroimaging data, image registration deserves particular attention due to its wide range of applications. Finding strategies to register together many images and analyze the differences between them can be a challenge, particularly given that different experimental designs require different registration strategies. Moreover, writing software that can handle different types of image registration pipelines in a flexible, reusable and extensible way can be challenging. In response to this challenge, we have created Pydpiper, a neuroimaging registration toolkit written in Python. Pydpiper is an open-source, freely available pipeline framework that provides multiple modules for various image registration applications. Pydpiper offers five key innovations. Specifically: (1) a robust file handling class that allows access to outputs from all stages of registration at any point in the pipeline; (2) the ability of the framework to eliminate duplicate stages; (3) reusable, easy to subclass modules; (4) a development toolkit written for non-developers; (5) four complete applications that run complex image registration pipelines ``out-of-the-box.'' In this paper, we will discuss both the general Pydpiper framework and the various ways in which component modules can be pieced together to easily create new registration pipelines. This will include a discussion of the core principles motivating code development and a comparison of Pydpiper with other available toolkits. We also provide a comprehensive, line-by-line example to orient users with limited programming knowledge and highlight some of the most useful features of Pydpiper. In addition, we will present the four current applications of the code.http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00067/fullNeuroimagingSoftwareimage registrationpythonpipeline |
| spellingShingle | Miriam eFriedel Matthijs C van Eede Jon ePipitone M Mallar Chakravarty M Mallar Chakravarty M Mallar Chakravarty Jason P Lerch Jason P Lerch Pydpiper: A Flexible Toolkit for Constructing Novel Registration Pipelines Frontiers in Neuroinformatics Neuroimaging Software image registration python pipeline |
| title | Pydpiper: A Flexible Toolkit for Constructing Novel Registration Pipelines |
| title_full | Pydpiper: A Flexible Toolkit for Constructing Novel Registration Pipelines |
| title_fullStr | Pydpiper: A Flexible Toolkit for Constructing Novel Registration Pipelines |
| title_full_unstemmed | Pydpiper: A Flexible Toolkit for Constructing Novel Registration Pipelines |
| title_short | Pydpiper: A Flexible Toolkit for Constructing Novel Registration Pipelines |
| title_sort | pydpiper a flexible toolkit for constructing novel registration pipelines |
| topic | Neuroimaging Software image registration python pipeline |
| url | http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00067/full |
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