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.

Document Object Model based XML Handling in ITK

In the medical simulation world the use of isosurfaces is a common action, as the information from some sources, e.g. CTs, is very well defined, and the isosurface can be easily set. Additionally, in any simulator shadows are a necessary addition to increase the users immersion as well as its depth perception. Unfortunately, the Visualization Toolkit does not offer these features, and so in this paper a modified vtkGPUVolumeRayCastMapper is presented. This modified version allows volumetric isosurface rendering as well as receiving shadows from polygons using the usual pipeline. 

Adding Refined Isosurface Rendering and Shadow Mapping to vtkGPUVolumeRayCastMapper

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.

Shape-based Interpolation of a Set of 2D Slices

This document describes a plug-in for Blender (www.blender.org) that allows to rasterize 3D mesh objects into 3D voxel data, i. e. it allows to voxelize Blender meshes. In 2D, this process can be compared to rasterization of vector graphics into pixel graphics. The voxelization is done by VTK (www.vtk.org) functions. A simple GUI allows to choose the type of voxelization and to specify necessary parameters. Depending on the type chosen, only the surface of the mesh objects is voxelized or the enclosed volume, i. e.“filled”. Beside the size of the output, one can specify if the result should be “anti-aliased” or not.
This paper is accompanied with the source code, input data, parameters and output data that the authors used for validating the script described in this paper.


Voxelizer plug-in for Blender

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.

Primal/Dual Mesh with Application to Triangular/Simplex Mesh and Delaunay/Voronoi

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).

An OpenCL implementation of the Gaussian pyramid and the resampler

This document describes an ITK implementation of an interactive method for tracing curvilinear structures.
The basic tools provided in this framework are an oriented flux-based tubularity measure and a geodesic path 
tracer that uses the fast marching algorithm. The framework is efficient and requires minimal user 
interaction to trace curvilinear structures such as vessels and neurites in 2D images and 3D image 
stacks.

Tubular Geodesics using Oriented Flux: An ITK Implementation

It is sometimes useful to be able to apply binary morphological operations, such as erosions and dilations, to labelled images in a fashion that preserves the labels. This article introduces a specialised class implementing parallel methods described in beare et al [2011] that provide very fast dilations by circles and spheres of arbitary size. Comparisons with other implementations using currently available building blocks are also made.


Parallel algorithms for erosion and dilation of label images.

This paper presents code for reading contours from DICOM RT structure set files into binary labels. This is a common requirement for transferring expert manual segmentations from radiotherapy treatment planning software into external image analysis environments (such as ITK). An implementation of RT structure set importing is provided with sample data from a prostate cancer radiotherapy planning volume. This is an update to the 2009 Insight Journal paper "Importing Contours from DICOM-RT Structure Sets" which worked with ITK 3.x and a local GDCM2 install.

Updates:
Mar 2013 Now correctly handles holes within structures. Thanks to Sebastian Steger for the code fix.

Importing Contours from DICOM-RT Structure Sets with ITK4

In today’s medicine a lot of research revolves around the combination of different imaging and tracking modalities to form a new system for Image-Guided Therapy. Such systems can help to overcome shortcomings of the individual techniques or create new kinds of possible use cases. To ease the development of a hybrid modality we have created a generic, portable, lightweight, and easily extensible, client-server based framework, implemented in C++, to control the communication between multiple imaging and tracking devices. Our framework Computer Aided Medical Procedures Communication (CAMPCom), allows developers of hybrid systems to focus on the most important implementation aspects by freeing them from the more generic tasks of data serialization and exchange. The framework is openly available on http://campar.in.tum.de/Main/CAMPCom