scholarly journals Computing Textural Feature Maps for N-Dimensional images

2017 ◽  
Author(s):  
Jean-baptiste Vimort ◽  
Matthew Mccormick ◽  
Francois Budin ◽  
Beatriz Paniagua
Keyword(s):  
Texture Analysis ◽  
Input Data ◽  
Source Code ◽  
Fundamental Principle ◽  
Textural Features ◽  
Neighborhood Size ◽  
Feature Maps ◽  
Output Data ◽  
Scientific Publications ◽  
Run Lengths

This document describes a new remote module implemented for the Insight Toolkit ITK, itkTextureFeatures. This module contains two texture analysis filters that are used to compute feature maps of N-Dimensional images using two well-known texture analysis methods. The two filters contained in this module are itkScalarImageToTextureFeaturesImageFilter (which computes textural features based on intensity-based co-occurrence matrices in the image) and itkScalarImageToRunLengthFeaturesImageFilter (which computes textural features based on equally valued intensity clusters of different sizes or run lengths in the image). The output of this module is a vector image of the same size than the input that contains a multidimensional vector in each pixel/voxel. Filters can be configured based in the locality of the textural features (neighborhood size), offset directions for co-ocurrence and run length computation, the number of bins for the intensity histograms, the intensity range or the range of run lengths. This paper is accompanied with the source code, input data, parameters and output data that we have 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.

scholarly journals N-Dimensional Computation of Strain Tensor Images in the Insight Toolkit

2017 ◽  
Author(s):  
Matthew Mccormick
Keyword(s):  
Image Registration ◽  
Constitutive Model ◽  
Displacement Field ◽  
Input Data ◽  
Source Code ◽  
Strain Tensor ◽  
Fundamental Principle ◽  
Local Deformation ◽  
Output Data ◽  
Scientific Publications

Strain quantifies local deformation of a solid body. In medical imaging, strain reflects how tissue deforms under load. Or, it can quantify growth or atrophy of tissue, such as the growth of a tumor. Additionally, strain from the transformation that results from image-to-image registration can be applied as an input to a biomechanical constitutive model.This document describes N-dimensional computation of strain tensor images in the Insight Toolkit (ITK), www.itk.org. Two filters are described. The first filter computes a strain tensor image from a displacement field image. The second filter computes a strain tensor image from a general spatial transform. In both cases, infinitesimal, Green-Lagrangian, or Eulerian-Almansi strain can be generated.This paper is accompanied with the source code, input data, parameters and output data that the authors 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.

scholarly journals Iterative Smoothing of Field Data in Spherical Meshes

2010 ◽  
Author(s):  
Luis Ibanez ◽  
B.t. thomas Yeo ◽  
Polina Golland
Keyword(s):  
Vector Field ◽  
Scalar Field ◽  
Input Data ◽  
Field Data ◽  
Source Code ◽  
Fundamental Principle ◽  
Mesh Smoothing ◽  
Output Data ◽  
Scientific Publications

This document describes a contribution to the Insight Toolkit intended to smooth the values of Field data associated with the nodes of a Spherical Mesh. The Mesh Smoothing filters contributed here do not modify the geometry or the topology of the Mesh. They act only upon the pixel data values associated with the nodes. Two filters are presented, one that smooths scalar field data, and a second one that smooths vector field data. 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.

scholarly journals Spherical Thin Plate Spline Mesh Filter

2012 ◽  
Author(s):  
Wen Li ◽  
Vincent Magnotta
Keyword(s):  
Thin Plate ◽  
Input Data ◽  
Source Code ◽  
Spherical Geometry ◽  
Fundamental Principle ◽  
Thin Plate Spline ◽  
Output Data ◽  
Scientific Publications ◽  
And Topology

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.

scholarly journals STL file format MeshIO class for ITK

2014 ◽  
Author(s):  
Luis Ibanez
Keyword(s):  
Input Data ◽  
Source Code ◽  
Fundamental Principle ◽  
File Format ◽  
Output Data ◽  
Scientific Publications ◽  
Reading And Writing ◽  
Stl File ◽  
3D Space

This document describes the implementation of an ITK class to support the reading and writing of Meshes in STL file format. The Meshes are assumed to contain 2D manifolds embedded in a 3D space. In practice, it would be desirable to use this class mostly to read and write QuadEdgeMeshes.This paper is accompanied with the source code, input data, parameters and output data that the authors 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.

scholarly journals CartesianToPolar and PolarToCartesian Image Filters

2019 ◽  
Author(s):  
Bhavya Ajani ◽  
Sikander Sharda
Keyword(s):  
Image Processing ◽  
Input Data ◽  
Source Code ◽  
Fundamental Principle ◽  
Polar Space ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Output Data ◽  
Scientific Publications ◽  
Image Filters

In this paper, we describe a set of filters, implemented in the Insight Toolkit www.itk.org, for converting an image from Cartesian co-ordinate space to Polar co-ordinate space and vice-versa. Cartesian to Polar conversion of an image is a useful operation in preprocessing stage of certain image-processing algorithm where feature of interest has simplified representation in the polar space. This paper is accompanied with the source code, input data, parameters and output data that the authors 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.

scholarly journals Computing Bone Morphometric Feature Maps from 3-Dimensional Images

2017 ◽  
Author(s):  
Jean-baptiste Vimort ◽  
Matthew Mccormick ◽  
Beatriz Paniagua
Keyword(s):  
Feature Vector ◽  
Source Code ◽  
Fundamental Principle ◽  
Input Image ◽  
Feature Maps ◽  
Output Data ◽  
Scientific Publications ◽  
3 Dimensional ◽  
Morphometric Feature ◽  
Internal Architecture

This document describes a new remote module implemented for the Insight Toolkit (ITK), itkBoneMorphometry. This module contains bone analysis filters that compute features from N-dimensional images that represent the internal architecture of bone. The computation of the bone morphometry features in this module is based on well known methods. The two filters contained in this module are itkBoneMorphometryFeaturesFilter. which computes a set of features that describe the whole input image in the form of a feature vector, and itkBoneMorphometryFeaturesImageFilter, which computes an N-D feature map that locally describes the input image (i.e. for every voxel). itkBoneMorphometryFeaturesImageFilter can be configured based in the locality of the desired morphometry features by specifying the neighborhood size. This paper is accompanied by the source code, the input data, the choice of parameters and the output data that we have used for validating the algorithms described. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results.

scholarly journals Histogram Matching Mesh Filter

2010 ◽  
Author(s):  
Wen Li ◽  
Vincent Magnotta
Keyword(s):  
Input Data ◽  
Source Code ◽  
Fundamental Principle ◽  
Output Data ◽  
Scientific Publications ◽  
Histogram Matching ◽  
Input Source

This documents describes the filter itk::HistogramMatchingQuadEdgeMeshFilter. It takes an input (source) mesh and a reference mesh, normalizes the scalar values between two meshes by histogram matching, and generates an output mesh which has a similar histogram as the input mesh. 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.

scholarly journals Helper class for initializing the grid parameters of a BSpline deformable transform by using an image as reference

2009 ◽  
Author(s):  
Luis Ibanez ◽  
Matt Turek ◽  
Stephen Aylward ◽  
Michel Audette
Keyword(s):  
Input Data ◽  
Source Code ◽  
Fundamental Principle ◽  
Output Data ◽  
Scientific Publications

This document describes a simple helper class intended for making easy to initialize the grid parameters of a BSplineDeformableTranform. 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.

scholarly journals Introduction to ITK Resample In-Place Image Filter

2010 ◽  
Author(s):  
Wei Lu ◽  
Hans Johnson
Keyword(s):  
Input Data ◽  
Source Code ◽  
Physical Space ◽  
Fundamental Principle ◽  
Input Image ◽  
Space Representation ◽  
Output Data ◽  
Scientific Publications ◽  
Image Filter ◽  
Place Image

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.

scholarly journals Mesh Similarity Calculator

2010 ◽  
Author(s):  
Wen Li ◽  
Vincent Magnotta
Keyword(s):  
Input Data ◽  
Source Code ◽  
Fundamental Principle ◽  
Jaccard Similarity ◽  
Output Data ◽  
Scientific Publications

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.

Sign in / Sign up

Export Citation Format

Share Document