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dc.contributor.authorTrezise, Melissaen
dc.date2013-08-05 10:15:16.607
dc.date.accessioned2013-08-06T21:23:37Z
dc.date.available2013-08-06T21:23:37Z
dc.date.issued2013-08-06
dc.identifier.urihttp://hdl.handle.net/1974/8148
dc.descriptionThesis (Master, Computing) -- Queen's University, 2013-08-05 10:15:16.607en
dc.description.abstractThe Insight Segmentation and Registration Toolkit (ITK) is a highly utilized open source medical imaging library. Written in C++, ITK provides chiefly the functionality to register, segment, and filter medical images. Although extremely powerful, ITK has a very steep learning curve for users with little or no background in programming. It was for this reason that SimITK was developed. SimITK wraps ITK into the model driven engineering environment Simulink, a part of the Matlab development suite. The first released version of SimITK was a proof of concept, and demonstrated that ITK could be wrapped successfully in Simulink. Very few segmentation and registration functions were available and the system was based on ITK version 3 with a semi-automatic wrapping procedure. In this thesis a new version of SimITK is presented that includes thirty-seven image filter, twelve optimizer, and nineteen transform classes from ITK version 4 which are successfully wrapped and tested. These classes were chosen to represent a broad range of usability (in the case of the filters) and to allow for greater flexibility when creating registration pipelines by having more options for optimizers, transforms, and metrics. Many usability improvements were also implemented for the registration pipeline, including providing the user with the metric value while executing a registration model and allowing the output image size to be specified for certain filters. In order for SimITK to transition to a usable research tool, several usability improvements were needed. These included transitioning from wrapping ITK version 3 to ITK version 4, fully automating the wrapping process, and usability modifications to the registration pipeline including a metric value output. These implementations of an automated wrapping procedure for ITK version 4, and improved usability of the registration pipeline have propelled SimITK on a path towards a usable research tool. The author will be creating a release of these changes, updating installation documentation, and updating tutorials which are available at www.SimITKVTK.comen
dc.language.isoengen
dc.relation.ispartofseriesCanadian thesesen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectMedical Imagingen
dc.subjectSimITKen
dc.subjectITKen
dc.subjectModel Driven Engineeringen
dc.titleSimITK: Model Driven Engineering for Medical Imagingen
dc.typethesisen
dc.description.degreeM.Sc.en
dc.contributor.supervisorMousavi, Parvinen
dc.contributor.supervisorAbolmaesumi, Purangen
dc.contributor.supervisorCordy, James R.en
dc.contributor.supervisorGobbi, Daviden
dc.contributor.departmentComputingen
dc.degree.grantorQueen's University at Kingstonen


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