http://www.midasjournal.org The MIDAS journal Copyright www.midasjournal.org http://www.midasjournal.org/images/IJLogo2.gif http://www.midasjournal.org Thu, 02 Sep 2010 03:16:36 -0400 Thu, 02 Sep 2010 03:16:36 -0400 http://www.midasjournal.org//browse/publication/644 This article provides an implementation of the symmetric log-domain diffeomorphic image registration algorithm, or symmetric demons algorithm for short. It generalizes Thirion's demons and the diffeomorphic demons algorithm. The main practical advantages of the symmetric demons with respect to the other demons variants is that is provides the inverse of the spatial transformation at no additional computational cost and ensures that the registration of image A to image B provides the inverse of the registration from image B to image A. The algorithm works completely in the log-domain, i.e. it uses a stationary velocity field to encode the spatial transformation as its exponential. Within the Insight Toolkit (ITK), the classical demons algorithm is implemented as part of the finite difference solver framework. Our code reuses and extends this generic framework. The source code is composed of a set of reusable ITK filters and classes together with their unit tests. We also provide a small example program that allows the user to compare the different variants of the demons algorithm. This paper gives an overview of the algorithm, an overview of its implementation and a small user guide to ease the use of the registration executable. Tue, 09 Feb 2010 00:00:00 -0500 http://www.midasjournal.org//browse/publication/644 This article provides an implementation of the symmetric log-domain diffeomorphic image registration algorithm, or symmetric demons algorithm for short. It generalizes Thirion's demons and the diffeomorphic demons algorithm. The main practical advantages of the symmetric demons with respect to the other demons variants is that is provides the inverse of the spatial transformation at no additional computational cost and ensures that the registration of image A to image B provides the inverse of the registration from image B to image A. The algorithm works completely in the log-domain, i.e. it uses a stationary velocity field to encode the spatial transformation as its exponential. Within the Insight Toolkit (ITK), the classical demons algorithm is implemented as part of the finite difference solver framework. Our code reuses and extends this generic framework. The source code is composed of a set of reusable ITK filters and classes together with their unit tests. We also provide a small example program that allows the user to compare the different variants of the demons algorithm. This paper gives an overview of the algorithm, an overview of its implementation and a small user guide to ease the use of the registration executable. Tue, 09 Feb 2010 00:00:00 -0500 http://www.midasjournal.org//browse/publication/755 ITK is one of the most powerful image segmentation and registration libraries available as an open source toolkit. Motivated by the recent popularization of the iPhone, iPod touch, and iPad, in this work, we describe the set of required steps for integrating the ITK framework into Apple’s iOS mobile operating system. Our focus in this paper is on the process of importing the C++ based ITK to the Objective-C based iOS, and creating a simple application that demonstrates the ITK libraries are integrated. This paper brings to the reader a user-manual on how to integrate the ITK libraries into iOS applications and code. We present here the series of steps we performed in order to import the ITK libraries as well as report the results of importing them under different versions of the iOS and under different architectures (the Simulator and Device architecture). Wed, 31 Dec 1969 19:00:00 -0500 http://www.midasjournal.org//browse/publication/752 This documents is about the filter itk::ScalarQuadEdgeMeshToListAdaptor. It takes the input mesh and generates a list of measurement vectors according to the scalars of the mesh. The list can be fed into itk::Statistics::SampleToHistogramFilter [1, 2] to generate a histogram about the scalars on the input mesh. This paper is accompanied with the source code, input data, parameters and output data that we used for validating the algorithm described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results. Wed, 31 Dec 1969 19:00:00 -0500 http://www.midasjournal.org//browse/publication/751 This article describes the filter itk::AssignScalarValuesQuadEdgeMeshFilter. It takes two meshes, one as an input and the other as a source to assign scalar values of the nodes from the source mesh to the input mesh. Both of the two meshes should have the same number of nodes. This paper is accompanied with the source code, input data, parameters and output data that we used for validating the algorithm described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results. Wed, 31 Dec 1969 19:00:00 -0500 http://www.midasjournal.org//browse/publication/750 This documents is about the filter itk::RescaleScalarsQuadEdgeMeshFilter. It takes an input mesh and generates an output mesh with user specifying scalar values in the range of [min;max]. This paper is accompanied with the source code, input data, parameters and output data that we used for validating the algorithm described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results. Wed, 31 Dec 1969 19:00:00 -0500 http://www.midasjournal.org//browse/publication/749 This documents describes the filter itk::HistogramMatchingQuadEdgeMeshFilter. It takes an input (source) mesh and a reference mesh, normalizes the scalar values between two meshes by histogram matching, and generates an output mesh which has a similar histogram as the input mesh. This paper is accompanied with the source code, input data, parameters and output data that we used for validating the algorithm described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results. Wed, 31 Dec 1969 19:00:00 -0500 http://www.midasjournal.org//browse/publication/753 The deconvolution, also called deblurring, tries to revert the optical distortion introduced during the aquisition of the image. It is a family of image processing which can be classed in the larger family of image restoration. Deconvolution is a very difficult problem, and many algorithms have been proposed to solve it, with different strenght and weakness which may depend on the context where they are used. As a consequence, it is desirable to have several algorithms available when trying to restore some images. The different algorithms are often built on a similar principle, making possible to share a large part of their API in their implementation. Also, the most generic operations related to deconvolution should be reusable in order to avoid code duplication and ease the implementation of new algorithms. In this contribution, the infrastructure for the implementation of several deconvolution algorithms is proposed. Based on this infrastructure, twelve simple deconvolution algorithms of reference are also provided. Wed, 31 Dec 1969 19:00:00 -0500 http://www.midasjournal.org//browse/publication/751 This article describes the filter itk::AssignScalarValuesQuadEdgeMeshFilter. It takes two meshes, one as an input and the other as a source to assign scalar values of the nodes from the source mesh to the input mesh. Both of the two meshes should have the same number of nodes. This paper is accompanied with the source code, input data, parameters and output data that we used for validating the algorithm described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results. Wed, 31 Dec 1969 19:00:00 -0500 http://www.midasjournal.org//browse/publication/750 This documents is about the filter itk::RescaleScalarsQuadEdgeMeshFilter. It takes an input mesh and generates an output mesh with user specifying scalar values in the range of [min;max]. This paper is accompanied with the source code, input data, parameters and output data that we used for validating the algorithm described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results. Wed, 31 Dec 1969 19:00:00 -0500 http://www.midasjournal.org//browse/publication/749 This documents describes the filter itk::HistogramMatchingQuadEdgeMeshFilter. It takes an input (source) mesh and a reference mesh, normalizes the scalar values between two meshes by histogram matching, and generates an output mesh which has a similar histogram as the input mesh. This paper is accompanied with the source code, input data, parameters and output data that we used for validating the algorithm described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results. Wed, 31 Dec 1969 19:00:00 -0500