The insight journal最新文献

{"title":"An ITK Implementation of a Diffusion Tensor Images Resampling Filter","authors":"François Budin, S. Bouix, M. Shenton, M. Styner, I. Oguz","doi":"10.54294/brogba","DOIUrl":"https://doi.org/10.54294/brogba","url":null,"abstract":"This paper describes the implementation of a resampling filter for Diffusion Tensor Images (DTI) in the Insight ToolKit (ITK). ITK already contains a filter for resampling scalar and vector images as well as several transformation and interpolation classes. However, due to the directional nature of DT images, using the existing classes would result in losing the structural information of the image. We developed a new resampling filter, specific to DTI, that preserves the structure by applying a rotation directly on the tensors while performing the transformation of the image. New transformation and interpolator classes have also been implemented to handle tensors correctly. The new transformation classes are based on algorithms described by D.C. Alexander et al. Finally, three filters have been written to correct symmetric semi-definite matrices that would no longer be positive after the resampling process and project them into the tensors’ space. In addition, a software based on the new classes has been developed and is provided with this article.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71184048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An OpenCL implementation of the Gaussian pyramid and the resampler","authors":"D. Shamonin, M. Staring","doi":"10.54294/j5h811","DOIUrl":"https://doi.org/10.54294/j5h811","url":null,"abstract":"Nonrigid image registration is an important, but resource demanding and time-consuming task in medical image analysis. This limits its application in time-critical clinical routines. In this report we explore acceleration of two time-consuming parts of a registration algorithm by means of parallel processing using the GPU. We built upon the OpenCL-based GPU image processing framework of the recent ITK4 release, and implemented Gaussian multi-resolution strategies and a general resampling framework. We evaluated the performance gain on two multi-core machines with NVidia GPUs, and compared to an existing ITK4 CPU implementation. A speedup factor of ~2-4 was realized for the multi-resolution strategies and a speedup factor of ~10-46 was achieved for resampling, for larger images (~10^8 voxels).","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71187517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Primal/Dual Mesh with Application to Triangular/Simplex Mesh and Delaunay/Voronoi","authors":"H. Irshad, S. Rigaud, A. Gouaillard","doi":"10.54294/9lt70e","DOIUrl":"https://doi.org/10.54294/9lt70e","url":null,"abstract":"This document describes an extension of ITK to handle both primal and dual meshes simultaneously. This paper describe in particular the data structure, an extension of itk::QuadEdgeMesh, a filter to compute and add to the the structure the dual of an existing mesh, and an adaptor which let a down- ward pipeline process the dual mesh as if it was a native itk::QuadEdgeMesh. The new data structure, itk::QuadEdgeMeshWithDual, is an extension of the already existing itk::QuadEdgeMesh, which already included by default the due topology, to handle dual geometry as well. Two types of primal meshes have been specifically illustrated: triangular / simplex meshes and Voronoi / Delaunay. A functor mechanism has been implemented to allow for different kind of computation of the dual geometry. This paper is accompanied with the source code and examples.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71182616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shape-based Interpolation of a Set of 2D Slices","authors":"C. Boydev, D. Pasquier, F. Derraz, L. Peyrodie, A. Taleb-Ahmed, J. Thiran","doi":"10.54294/o9yvms","DOIUrl":"https://doi.org/10.54294/o9yvms","url":null,"abstract":"We implemented the shape-based interpolation method described by Raya and Udupa in 1990 for three-dimensional images, and created two standalone filters using the Insight Toolkit ITK. The image to be interpolated must be a 3D binary image which represents an object as a series of 2D slices with pixel values at 1 inside the object and 0 outside by convention. The first filter takes as input a 3D binary image wherein the object of interest is represented in full, that is, on all contiguous slices that comprise it. Such filter yields an upsampled 3D binary image. The second filter takes as input a 3D binary image wherein the object of interest is represented only on certain slices that are regularly spaced. It yields a 3D binary image of the same size as that of the input and wherein the object is represented on all contiguous slices that comprise it. This paper is provided with the source code as well as the data used for validation.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71189846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unwarping Echo Planar Images Using CMTK","authors":"T. Rohlfing","doi":"10.54294/qffl03","DOIUrl":"https://doi.org/10.54294/qffl03","url":null,"abstract":"This document describes the workflow for unwarping echo planar MR images (EPI), in particular diffusion-weighted images, using an acquisition method with reversed phase encoding and the tools of the Computational Morphometry Toolkit (CMTK). This technique requires an additional acquisition (additional b=0 image for diffusion imaging) with reversed phase encoding direction, but no field map. Simple 6-direction diffusion data are provided with this article for demonstration.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71191417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Document Object Model based XML Handling in ITK","authors":"R. Gong, Z. Yaniv","doi":"10.54294/uzvmer","DOIUrl":"https://doi.org/10.54294/uzvmer","url":null,"abstract":"The Insight Segmentation and Registration Toolkit (ITK) previously provided a framework for parsing Extensible Markup Language (XML) documents using the Simple API for XML (SAX) framework. While this programming model is memory efficient, it places most of the implementation burden on the user. We provide an implementation of the Document Object Model (DOM) framework for parsing XML documents. Using this model, user code is greatly simplified, shifting most of the implementation burden from the user to the framework. The provided implementation consists of two tiers. The lower level tier provides functionality for parsing XML documents and loading the tree structure into memory. It then allows the user to query and retrieve specific entries. The upper tier uses this functionality to provide an interface for mimicking a serialization and de-serialization mechanism for ITK objects. The implementation described in this document was incorporated into ITK as part of release 4.2.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71192961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An implementation of the minimization of region-scalable fitting energy levelsets","authors":"Hui Tang, Reinhard Hameeteman, A. Gelas, T. van Walsum","doi":"10.54294/lyf209","DOIUrl":"https://doi.org/10.54294/lyf209","url":null,"abstract":"Intensity inhomogeneities often occur in medical images, especially when using magnetic resonance imaging. In these images, the standard Chan-and-Vese levelset segmentation method may not work properly, as it assumes constant intensity distributions for foreground and background. Recently, a novel method was published that models the intensities as piece-wise smooth, and thus is more suitable to segment images with intensity homogeneities. However, this method was not yet implemented in ITK. This submission introduces our implementation of the region-scalable-fitting levelset segmentation method within the ITKv4 levelset framework.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71188213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An ITK Implementation of Physics-based Non-rigid Registration Method","authors":"Yixun Liu, A. Kot, F. Drakopoulos, Andrey Fedorov, A. Enquobahrie, O. Clatz, N. Chrisochoides","doi":"10.54294/f9hilk","DOIUrl":"https://doi.org/10.54294/f9hilk","url":null,"abstract":"As part of the ITK v4 project efforts, we have developed ITK filters for physics-based non-rigid registration (PBNRR), which satisfies the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid registration, and reduce execution time using GPU and multi-core accelerators. The implementation has three main components: (1) Feature Point Selection, (2) Block Matching (mapped to both multi-core and GPU processors), and (3) a Robust Finite Element Solver. The use of multi-core and GPU accelerators in ITK v4 provides substantial performance improvements. For example, in average for the non-rigid registration of brain MRIs, the performance of the Block Matching filter is about 12 times faster when 12 hyperthreaded multi-cores are used and about 540 times faster when the Quadro 6000 with 448 threads is used in Dell Workstation.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71185913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Next Generation of the Java Image Science Toolkit (JIST): Visualization and Validation.","authors":"Bo Li,&nbsp;Frederick Bryan,&nbsp;Bennett A Landman","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Modern medical imaging analyses often involve the concatenation of multiple steps, and neuroimaging analysis is no exception. The Java Image Science Toolkit (JIST) has provided a framework for both end users and engineers to synthesize processing modules into tailored, automatic multi-step processing pipelines (\"layouts\") and rapid prototyping of module development. Since its release, JIST has facilitated substantial neuroimaging research and fulfilled much of its intended goal. However, key weaknesses must be addressed for JIST to more fully realize its potential and become accessible to an even broader community base. Herein, we identify three core challenges facing traditional JIST (JIST-I) and present the solutions in the next generation JIST (JIST-II). First, in response to community demand, we have introduced seamless data visualization; users can now click 'show this data' through the program interfaces and avoid the need to locating files on the disk. Second, as JIST is an open-source community effort by-design; any developer may add modules to the distribution and extend existing functionality <i>for release.</i> However, the large number of developers and different use cases introduced instability into the overal JIST-I framework, causing users to freeze on different, incompatible versions of JIST-I, and the JIST community began to fracture. JIST-II addresses the problem of compilation instability by performing continuous integration checks nightly to ensure community implemented changes do not negatively impact overall JIST-II functionality. Third, JIST-II allows developers and users to ensure that functionality is preserved by running functionality checks nightly using the continuous integration framework. With JIST-II, users can submit layout test cases and quality control criteria through a new GUI. These test cases capture all runtime parameters and help to ensure that the module produces results within tolerance, despite changes in the underlying architecture. These three \"next generation\" improvements increase the fidelity of the JIST framework and enhance utility by allowing researchers to more seamlessly and robustly build, manage, and understand medical image analysis processing pipelines.</p>","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"2012 ","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2012-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4181667/pdf/nihms-431349.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32722316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incremental Delaunay Triangulation","authors":"Stéphane Rigaud, A. Gouaillard","doi":"10.54294/m1v32y","DOIUrl":"https://doi.org/10.54294/m1v32y","url":null,"abstract":"This document describes the implementation in ITK of the Incremental Delaunay Triangulation algorithm. Using the Straight Walk in Triangulation function, the exact discrete geometrical orientation predicate, and the itk::QuadEdgeMesh API of ITK , we propose a geometrically exact and robust implementation that, from a given 2-dimensional itk::PointSet, incrementally constructs the corresponding 2-dimensional Delaunay Triangulation as an itk::QuadEdgeMesh.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71188896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}