Kernel based filtering is one of the fundamental tools of image
analysis and processing. A number of approaches have been developed
over the years that allow efficient implementation of such filters
even when the kernel size is large. This article reviews some of these
methods and introduces their ITK implementations.

Efficient implementation of kernel filtering

This paper describes an image processing prototyping environment called SharpImage. SharpImage is a stand-alone Windows application geared towards the pre-processing and creation of volume illustrations, although other generic tasks are inherently supported. The user interacts with the environment using a command console, and can view images as a series of slices or through volume rendering. We describe the design and introduce functionality using a number of examples. We have found the environment useful for prototyping a range of image processing tasks and provide the source-code in the hope others may also find it useful.

SharpImage: An Image Processing Prototyping Environment

This is a companion paper describing the process and parameters for tagged volume rendering of the heart. We firstly review the relevant concepts and consider the problem of visualising the coronary arteries from computed tomography angiography (CTA) images. We then discuss the implementation using the SharpImage prototyping environment. Finally, we list the set of commands capable of reproducing our results using the accompanying dataset.

Tagged Volume Rendering of the Heart: A Case Study

This paper describes vessel enhancing diffusion (VED) filters implemented 
using the Insight Toolkit (ITK). The filters are implementation of the 
VED algorithm developed by Manniesing et al . The VED algorithm follows a 
multiscale approach to enhance vessels using anisotropic diffusion scheme guided 
by vesselness measure at a pixel level. Vesselness is determined by geometrical 
analysis of the Eigen system of the Hessian matrix. For this purpose, a smoothed version of the Frangi's 
vesselness function is formulated. Experiments were conducted to evaluate the performance
of the VED filters in enhancing vessels in lung CT scan.

Vessel Enhancing Diffusion Filter

This paper presents an extension of the Visualization ToolKit dedicated to spatiotemporal data synchronization, visualization and management. It basically consists in a versatile library providing functionalities to help developers setting up sophisticated applications with minimal development effort. In the medical imaging context, various types of data are often encountered, which raises the need for adapted visualization and synchronization techniques. Moreover, the management of these data (organization, creation, deletion, access) can become a burden. We propose in vtkINRIA3D a strategy to synchronize interactions between datasets representations, to manipulate complex objects (e.g., neural fibers as obtained in DT-MRI), as well as a managing framework for organizing data (including temporal sequences). The efficiency of vtkINRIA3D is illustrated with two applications: MedINRIA (general medical image processing software) and CardioViz3D (cardiac image visualization). vtkINRIA3D is open-source, and comes with a set of examples, test data and softwares built upon it: http://www-sop.inria.fr/asclepios/software/vtkINRIA3D.

vtkINRIA3D: A VTK Extension for Spatiotemporal Data Synchronization, Visualization and Management

In this document it is described the implementation of the flux driven automatic centerline extraction
algorithm proposed by Bouix et al. in 2004. This is based on a skeletonisation algorithm initially
proposed by Siddiqi et al. in 2002, using properties of an average outward flux measure to distinguish
skeletal points from non-skeletal ones. This information is combined with a topology preserving thinning
procedure to obtain the final result. This implementation combines this skeletonisation algorithm with
other techniques as described in the paper of Bouix et al. to produce an ITK filter that generates as output
the skeleton, as a binary object represented in an image, of the input surface, represented as a distance
transform image. In this work is described this medial curve extraction procedure following the ITK
philosophy.

Flux driven medial curve extraction

Performance validation of nonlinear registration algorithms is a difficult problem due to the lack of a suitable ground truth in most applications. However, the ill-posed nature of the nonlinear registration problem and the large space of possible solutions makes the quantitative evaluation of algorithms extremely
important. We argue that finding a standardized way of performing evaluation and comparing existing and new algorithms currently is more important than inventing novel methods. While there are already existing evaluation frameworks for nonlinear inter-subject brain registration applications, there is still a lack of protocols for intra-subject studies or soft tissue organs. In this work we present
such a framework which is designed in an ”open-source” and ”open-data” manner around the Insight Segmentation & Registration Toolkit. The goal of our work is to provide the research community with the basis framework that should be extended by interested people in a community effort to gain importance for evaluation studies. We demonstrate our proposed framework on a sample evaluation and release its implementation and associated tools to the public domain.

A Framework for Comparison and Evaluation of Nonlinear Intra-Subject Image Registration Algorithms

Open Science includes access to both open source software/methodologies and open data. While there has been progress in open image databases, the results of these efforts are under-reported. As such, imaging scientists are unaware of the available data. In addition, many researchers are interested in providing their data to the greater research community, but may be unaware of the process to release the data. The purpose of this paper is to describe our efforts in developing an open website which includes information on accessible medical image databases as well as some of the logistics for providing an open image database. Most importantly, the authors are requesting participation from the community to contribute to the Medical Image Database Repository (http://midr.org) in order to consolidate the collect knowledge of the community.

Data, data everywhere, nor an image to read - Finding open image databases.

This paper describes the ITK implementation of a transform initializer to produce a rigid 3-D transform able to center a given point on an arbitrary plane. The resultant transform allows the user to "look at" a point from a given direction. The resultant transform can also be used to obtain an oblique section: a single arbitrary 2-D slice through a 3-D image.

LookAt Transform Initializer and Oblique Section Image Filter

White matter tractography enables studies of fiber bundle characteristics. Stochastic tractography facilitates these investigations by providing a measure of confidence regarding the inferred fiber bundles. This article presents a multithreaded ITK stochastic tractography filter that will enable novel studies of fiber tract abnormalities. Additionally, we provide an easy to use command line interface for the filter that is compatible with the 3D Slicer visualization environment.