This documents is about the filter itkQuadEdgeMeshSimilarityCalculator. It takes inputs of two meshes and gives the similarity of the labels on them in two types of similarity measurements – Dice Similarity and Jaccard Similarity.
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.

Mesh Similarity Calculator

This documents is about the filter itk::WarpQuadEdgeMeshFilter. It takes two input meshes (fixed and moving meshes) and one deformation field. It produces one output mesh. Each point on the fixed mesh is warped according to the displacement vector saved in the deformation field and gets a scalar value assigned by interpolating the scalar value from the moving mesh. An interpolator is needed to apply this filter.
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.

Warp Mesh Filter

Expectation maximization (EM) is a common technique for estimating the parameters of a model after having collected observations of data generated by the model. We first explain the algorithm, then present our impelementation. We focus on estimation of the parameters of a Gaussian Mixture Model (GMM). The implementation is written in the VTK framework and is provided as a new class, vtkExpectationMaximization.

The code is hosted here: http://github.com/daviddoria/ExpectationMaximization for the time being.

Expectation Maximization of Gausian Mixture Models in VTK

Mean shift clustering is an excellent technique for clustering points when the number of clusters is not known. We present a implementation (vtkMeanShiftClustering) of the simplest version of the algorithm written in a VTK context.

The code is currently hosted at http://github.com/daviddoria/vtkMeanShiftClustering .

A Mean Shift Clustering Implementation for VTK

K-Means clustering is an excellent technique for clustering points when the number of clusters is known. We present a implementation (vtkKMeanClustering) of the algorithm written in a VTK context. We also implement the K-Means++ initialization method which finds the global optimum much more frequently than a naive/random initialization.

The code is currently hosted at http://github.com/daviddoria/KMeansClustering .

A K-Means++ Clustering Implementation for VTK

It is convenient to acquire data in a format which VTK can read directly. To enable this, we provide a wrapper of the Hokuyo UTM-30LX interface in a class vtkHokuyo. The code is currently hosted at git@github.com:daviddoria/vtkHokuyo.git. This class only works on Linux systems.

A VTK Interface for the Hokuyo UTM 30LX Laser Range Finder

Being able to quickly compute the inverse of a deformation ﬁeld is often useful in the context of medical image analysis. While ITK supports this functionality, the current algorithms are slow and do not always yield accurate results. In this paper we describe an ITK implementation of a ﬁxed point algorithm for the approximate inversion of deformation ﬁelds that was recently proposed by M. Chen and co-workers. The algorithm has been shown to be both faster and more accurate than those currently implemented in ITK.


Inverting deformation fields using a fixed point iteration scheme

The Random Sample Consensus (RANSAC) algorithm for robust parameter value estimation has been applied to a wide variety of parametric entities (e.g. plane, the fundamental matrix). In many implementations the algorithm is tightly integrated with code pertaining to a specific parametric object. In this paper we introduce a generic RANSAC implementation that is independent of the estimated object. Thus, the user is able to ignore outlying data elements potentially found in their input. To illustrate the use of the algorithm we implement the required components for estimating the parameter values of a hyperplane and hypersphere.


Random Sample Consensus (RANSAC) Algorithm, A Generic Implementation

In this document we present an ITK image filter that outputs a new image with identical voxel contents but with modified physical space representation. The physical space representation of an image is modified to reflect the physical space transform on the input image. The advantage of this filter is that it is free from interpolation error.
This paper is accompanied with the source code, input data, parameters and output data that the au- thors 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.

Introduction to ITK Resample In-Place Image Filter


We think about interoperability only in today’s terms. Looking ahead, the demands that future technologies will make on health information exchange could be large, as could the health because of interoperability. This paper would present the description on Healthcare Information System organizations and communities as a standard to underpin clinical information exchange. A number of signiﬁcant problems results are directly from the way the computable entries in clinical documents exchange represented currently. In this paper, the information exchange with other system and also supporting communication of electronic healthcare records across organization boundaries. The CCD is an XML-based specification for exchange of clinical summary information. The HL7 Reference Information Models expressed in the Clinical Document Architecture Release 2 (CDA R2), an information exchange specification generic to any type of clinical information. Hence, the patient’s health information is easily communicated points of care and improves quality services. 
