The insight journal最新文献

{"title":"Next Generation of the Java Image Science Toolkit (JIST): Visualization and Validation.","authors":"Bo Li, Frederick W. Bryan, B. Landman","doi":"10.54294/ihtu4s","DOIUrl":"https://doi.org/10.54294/ihtu4s","url":null,"abstract":"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 for release. 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.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"2012 1","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2012-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71187215","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":"Efficient N-Dimensional surface estimation using Crofton formula and run-length encoding","authors":"G. Lehmann, D. Legland","doi":"10.54294/wdu86d","DOIUrl":"https://doi.org/10.54294/wdu86d","url":null,"abstract":"Unlike the measure of the area in 2D or of the volume in 3D, the perimeter and the surface are not easily measurable in a discretized image. In this article we describe a method based on the Crofton formula to measure those two parameters in a discritized image. The accuracy of the method is discussed and tested on several known objects. An algorithm based on the run-length encoding of binary objects is presented and compared to other approaches. An implementation is provided and integrated in the LabelObject/LabelMap framework contributed earlier by the authors.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71193474","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":"Spherical Thin Plate Spline Mesh Filter","authors":"Wen Li, Vincent Magnotta","doi":"10.54294/6ahrby","DOIUrl":"https://doi.org/10.54294/6ahrby","url":null,"abstract":"This document describes a contribution to the Insight Toolkit intended to perform landmark-based registration on two meshes. The method implemented here is restricted to meshes with a spherical geometry and topology. Please refer Wahba’s paper for the mathematical details and Zou’s paper for the applications. 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.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71180906","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":"Walk In A Triangulation : Straight Walk","authors":"Stéphane Rigaud, A. Gouaillard","doi":"10.54294/esnq73","DOIUrl":"https://doi.org/10.54294/esnq73","url":null,"abstract":"This document describes the implementation in ITK of the Straight Walk in a Triangulation algorithm proposed by Devillers et al. Using the exact discrete geometrical orientation predicate, and the itk::QuadEdgeMesh API of ITK, we propose an efficient implementation that locates a point in a triangulated mesh structure. This paper is accompanied with the source code and examples that should provide enough details for users. This work has for principal intended an exact and robust implementation of a Delaunay triangulation / Voronoi tesselation in ITK, which will be presented in a separate paper, once done.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71185390","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":"Multilocal Creaseness Measure","authors":"Sergio Vera, Debora Gil, Antonio López, Miguel Á. González","doi":"10.54294/ynt3ar","DOIUrl":"https://doi.org/10.54294/ynt3ar","url":null,"abstract":"This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71194594","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":"The TVDMFFDVR Algorithm","authors":"N. Tustison, B. Avants","doi":"10.54294/tr49io","DOIUrl":"https://doi.org/10.54294/tr49io","url":null,"abstract":"The recent ITKv4 refactoring includes several enhancements to the existing registration framework. These additional transform classes provide access to mappings described by dense displacement fields and their corresponding optimization which complement the popular free-form deformation (FFD) ap- proach already in ITK. Innovation motivated by previous work [5] and recent diffeomorphic image regis- tration developments in which the characteristic velocity field is represented by spatiotemporal B-splines [2], resulted in a diffeomorphic B-spline-based image registration algorithm combining and extending these techniques which we make available in ITK through the gerrit system. Additionally, we include two command line tools showcasing the new elements of the registration refactoring for 1) computing mappings between two images (antsRegistration) including the family of transforms discussed in this article and 2) applying those transformations to images (antsApplyTransforms). NB: The user must download the patch available at http://review.source.kitware.com/#/c/3606/ in or- der to compile the code accompanying this article.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2012-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71192436","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":"Principal Components Analysis of Scalar, Vector, and Mesh Vertex Data.","authors":"Michael Bowers,&nbsp;Laurent Younes","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This document describes a contribution to the Insight Toolkit intended to support the analysis of the principal components of data sets, optionally point data associated with the vertices of a mesh. This paper is accompanied with the source code, input data, parameters and output data that we used for validating the implementation described in this paper. This adheres to the fundamental principle that scientific publications must facilitate <b>reproducibility</b> of the reported results.</p>","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"2012 ","pages":"878"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3938194/pdf/nihms417264.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32169144","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":"A Threshold with Hysteresis","authors":"Sergio Vera, Frederic Pérez, Laura Lara, Miguel Á. González","doi":"10.54294/u9p515","DOIUrl":"https://doi.org/10.54294/u9p515","url":null,"abstract":"Thresholding is perhaps one of the most basic techniques in image processing. The Insight Toolkit (ITK) includes several threshold filters ranging from simple ones to Otsu based thresholding. Deep into the implementation of the Canny edge detection filter, ITK includes an implementation of hysteresis thresholding, but unfortunately this method can not be used as a generic filter. This paper presents an implementation of the hysteresis thresholding filter that can be used as a standalone ITK filter.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71192548","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":"Fuzzy Clustering Algorithms for Image Segmentation","authors":"A. Rey, A. Castro, B. Arcay","doi":"10.54294/9baij3","DOIUrl":"https://doi.org/10.54294/9baij3","url":null,"abstract":"In this document we present the implementation of three fuzzy clustering algorithms using the Insight Toolkit ITK. Firstly, we developed the conventional Fuzzy C-Means that will serve as the basis for the rest of the proposed algorithms. The next algorithms are the FCM with spatial constraints based on kernel-induced distance and the Modified Spatial Kernelized Fuzzy C-Means. Both of these introduce a Kernel function, replacing the Euclidean distance of the FCM, and spatial information into the membership function.These algorithms have been implemented in a threaded version to take advantage of the multicore processors. Moreover, providing an useful implementation make it possible that classes work with 2D/3D images, different kernels and spatial shapes.We included the source code as well as different 2D/3D examples, using several input parameters for the algorithms and obtaining the results generated on 2D/3D CT lung studies.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71182266","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":"Exact Geometrical Predicate: Point in circle","authors":"B. Moreau, A. Gouaillard","doi":"10.54294/vb4oi6","DOIUrl":"https://doi.org/10.54294/vb4oi6","url":null,"abstract":"This document describes the implementation in ITK of the “point in circle” geometrical predicate. Based on Jonathan Shewchuk’s work which implements an exact version of the predicate using standard floating point types and arithmetic, the implementation consist of an ITK wrapper around the public domain C routines made available by the author of the precedent paper. Wrapper using itk::PointSet, itk:CellInterface and itk:Mesh / itk:QuadEdgeMesh APIs are provided along with corresponding examples which should provide enough details for users to directly copy paste code in their application.The application in mind for us is an exact and robust implementation of a delaunay triangulation / voronoi tesselation in ITK, and will be presented in a separate paper.","PeriodicalId":89491,"journal":{"name":"The insight journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71193612","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}