bluuebunny/crossref_metadata_2025 huggingface dataset:
Fast BlockMatching Registration with Entropy-based Similarity
Authors: Suarez-Santana Eduardo , Nebot Rafael , Westin Carl-fredrik , Ruiz-Alzola Juan
Published: January 2022

This paper describes the implementation of a multidimensional block-matching nonrigid registration algorithm. The main features of the algorithm are its simplicity, its free form nature, the modularity of the similarity measure, which makes it possible using local entropy-based similarity measures and the avoidance of the optimization module. The algorithm implementation described in this paper is based on the method by Suarez et al. This paper, which has already been submitted to the Insight Journal, is accompanied with the source code, input data, parameters and output data used for validating the algorithm described in it.
A Mesh Front Iterator for VTK
Authors: Doria David
Published: January 2022

Region growing is a technique that can be used to propagate information over a mesh. We provide an iterator that can be used with vtkPointSet subclasses to traverse a mesh in a reasonable fashion. A “front” is emanated from a selected starting vertex, and the iterator provides the ID of the next vertex on this front.
level set segmentation using coupled active surfaces
Authors: Mosaliganti Kishore , Smith Benjamin , Gelas Arnaud , Gouaillard Alexandre , megason sean
Published: January 2022

An Insight Toolkit (ITK) processing framework for simultaneous segmentation of multiple objects using active contours without edges is presented in this paper. These techniques are also popularly referred to as multiphase methods. Earlier, we had an implemented the Chan and Vese [1] algorithm that uses level- sets to accomplish region segmentation in images with poor or no gradient information. The current work extends that submission to use multiple level sets that evolve concurrently. The basic idea is to partion the image into several sets of piecewise constant intensity regions. This work is in contrast to the level-set methods currently available in ITK which necessarily require gradient information and also necessarily segment a single object-of-interest. Similar to those methods, the methods presented in this paper are also made efﬁcient using a sparse implementation strategy that solves the contour evolution PDE at the level-set boundary. This work does not introduce any new ﬁlter but extends the earlier submitted to ﬁlters to process multiple objects. We include 2D/3D example code, parameter settings and show the results generated on a 2D cardiac image.
An alternative threading model for the Insight Toolkit
Authors: Blezek Daniel
Published: January 2022

This technical note presents an alternative threading model for the Insight Toolkit. The existing ITK threading model is based on a "scatter / gather" model and divides work evenly amongst all threads. Though suitable for many filters, considerations such as memory allocation per thread are important in some classes of filters. We propose to use the ZThread (http://sourceforge.net/projects/zthread/) library to explore a threading model based on an execution pool. The ZThread library is a cross platform, open source thread abstraction library loosely based on Java's threading model.
An ITK-based Implementation of the Stochastic Rank Correlation (SRC) Metric
Authors: Steininger Philipp , Neuner Markus , Birkfellner Wolfgang , Gendrin Christelle , Mooslechner Michaela , Bloch Christoph , Pawiro Supyianto , Sedlmayer Felix , Deutschmann Heinrich
Published: January 2022

Recently, Birkfellner et al. proposed a novel image-to-image merit function (stochastic rank correlation, SRC) for robust intensity-based 2D/3D image registration. In this work, we summarize the basic idea of SRC, and present a generic ITK-based implementation of this image-to-image metric including tests for software veriﬁcation. Moreover, we provide two simple examples that demonstrate the usage of this metric: a) within the native ITK 2D/3D image registration method, and b) within a recently published extended ITK-based 2D/3D registration framework. It is, however, important to note, that this paper neither covers a comprehensive evaluation of SRC, nor a comparison with other metrics. It rather shows that SRC appears to succeed on a femoral and a porcine data set in the course of ITK-based 2D/3D image registration.
Statismo - A framework for PCA based statistical models
Authors: Lüthi Marcel , Blanc Remi , Albrecht Thomas , Gass Tobias , Goksel Orcun , Büchler Philippe , Kistler Michael , Bousleiman Habib , Reyes Mauricio , Cattin Philippe , Vetter Thomas
Published: January 2022

This paper describes the Statismo framework, which is a framework for PCA based statistical models.Statistical models are used to describe the variability of an object within a population, learned from a set of training samples. Originally developed to model shapes, statistical models are now increasingly used to model the variation in different kind of data, such as for example images, volumetric meshes or deformation fields. Statismo has been developed with the following main goals in mind: 1) To provide generic tools for learning different kinds of PCA based statistical models, such as shape, appearance or deformations models. 2) To make the exchange of such models easier among different research groups and to improve the reproducibility of the models. 3) To allow for easy integration of new methods for model building into the framework. To achieve the first goal, we have abstracted all the aspects that are specific to a given model and data representation, into a user defined class. This does not only make it possible to use Statismo to create different kinds of PCA models, but also allows Statismo to be used with any toolkit and data format. To facilitate data exchange, Statismo defines a storage format based on HDF5, which includes all the information necessary to use the model, as well as meta-data about the model creation, which helps to make model building reproducible. The last goal is achieved by providing a clear separation between data management, model building and model representation. In addition to the standard method for building PCA models, Statismo already includes two recently proposed algorithms for building conditional models, as well as convenience tools for facilitating cross-validation studies. Although Statismo has been designed to be independent of a particular toolkit, special efforts have been made to make it directly useful for VTK and ITK. Besides supporting model building for most data representations used by VTK and ITK, it also provides an ITK transform class, which allows for the integration of Statismo with the ITK registration framework. This leverages the efforts from the ITK project to readily access powerful methods for model fitting.
Generating a Deformation Field from a Transform
Authors: Staring Marius
Published: January 2022

This document describes a new class that takes an and evaluates the deformation at points in a user-defined region. The class is implemented using the Insight Toolkit url{www.itk.org}.
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.
GoFigure and The Digital Fish Project: Open tools and open data for an imaging based approach to system biolgy
Authors: Gouaillard Alexandre , Brown Titus , Bronner-Fraser Marianne , Fraser Scott E. , Megason Sean G.
Published: January 2022

As part of the Center of Excellence in Genomic Science at Caltech, we have initiated the Digital Fish Project. Our goal is to use in toto imaging of developing transgenic zebrafish embryos on a genomic scale to acquire digital, quantitative, cell-based, molecular data suitable for modelling the biological circuits that turn an egg into an embryo. In toto imaging uses confocal/2-photon microscopy to capture the entire volume of organs and eventually whole embryos at cellular resolution every few minutes in living specimens thoughout their development. The embryos are labelled such that nuclei are one color and cell membranes another color to allow cells to be segmented and tracked as they move and divide. The use of a transgenic marker in a third color allows a variety of molecular data to be marked. In toto imaging generates 4-d image sets (xyzt) which can contain 100,000 to 1,000,000 images per experiment. We are developing a software package called GoFigure to visualize, segment, and analyze these very large image sets. GoFigure uses a MySQL database back end for managing storage of images and segmented objects and uses VTK and ITK for visualization and segmentation. We plan to use in toto imaging to digitize the complete expression and subcellular localization patterns of thousands of proteins throughout zebrafish embryogenesis. This genomic data, our zebrafish lines, and GoFigure will be distributed following the Open Data/Open Source model.
Visual Programming of VTK Pipelines in Simulink
Authors: Gobbi David , Mousavi Parvin , Campigotto Adam , Dickinson Andrew W. L. , Abolmaesumi Parvin
Published: January 2022

We have created a wrapper package named SimVTK that allows VTK, and third-party classes derived from VTK classes, to be seamlessly integrated with MATLAB’s Simulink interface. Our package generates a loadable Simulink module for each VTK class, which is then represented as a “block” on the Simulink canvas, and can be connected with other blocks to form a pipeline. Each block can be double-clicked to bring up a dialog box that allows introspection and control of the VTK class. After a VTK pipeline has been built, it can be run interactively from within Simulink. The outputs of the pipeline can be displayed in an interactive render window, written to a disk file, or exported to a MATLAB variable. Within Simulink, the VTK pipeline can also be connected to the ITK pipeline through the use of our SimITK package. We generate the VTK-Simulink wrapper automatically though the use of CMake build scripts, with XML as an intermediate representation of the VTK class interfaces.
Live-Wire-ing the Insight Toolkit with Intelligent Scissors
Authors: Tustison Nicholas J. , Yushkevich Paul , Gee James
Published: January 2022

Semi-automatic image segmentation algorithms depend on interaction with the user to accurately define a region of interest within an image. Once such method is a dynamic programming approach called {em Intelligent Scissors} developed by Mortenson and Barret cite{Mortensen1992,Mortensen1995,Barrett1996,Barrett1997}. Standard interaction involves the user-placement of a seed point on or near the boundary of the object to be extracted. Using a gradient-based cost function, a {em live-wire} image path from the seed point to a subsequently placed boundary point is determined. As this free point is manipulated with the mouse cursor, the live-wire boundary, which extends from the seed point to the varying free point, locks onto nearby edges within the image. Although some applications do not require such user-interaction (e.g. cite{Hu2001}) warranting inclusion within the toolkit, incorporating live-wire capabilities into ITK-SNAP cite{Yushkevich2006} has been discussed and, therefore, we would like to, as a preliminary step, vet the code within the ITK community.
Enabling ITK-based processing and 3D Slicer MRML scene management in ParaView
Authors: Enquobahrie Andinet , Bowers Michael , Ibanez Luis , Finet Julien , Audette Michel , Kolasny Anthony
Published: January 2022

This paper documents on-going work to facilitate ITK-based processing and 3D Slicer scene management in ParaView. We believe this will broaden the use of ParaView for high performance computing and visualization in the medical imaging research community. The effort is focused on developing ParaView plug-ins for managing VTK structures from 3D Slicer MRML scenes and encapsulating ITK filters for deployment in ParaView. In this paper, we present KWScene, an open source cross-platform library that is being developed to support implementation of these types of plugins. We describe the overall design of the library and provide implementation details and conclude by presenting a concrete example that demonstrates the use of the KWScene library in computational anatomy research at Johns Hopkins Center for Imaging Science.
ITK Neural Networks IO Classes
Authors: Venkatram Raghu
Published: January 2022

Classes to provide IO capabilities for the ITK Neural Networks library.
Zeiss (LSM) file format support
Authors: Malaterre Mathieu
Published: January 2022

This filter will allow support for file reading and writting in ITK for the Zeiss (LSM) file format.
Escher's Ants as Metaphor: Topological Marching for the Well-Composed, Genus Zero Crowd
Authors: Tustison Nicholas J. , Avants Brian , Siqueira Marcelo , Gee James
Published: January 2022

Topological considerations for segmentation results are important for such applications as proper brain segmentation from digital image data. We present an enhancement of the FastMarchingImageFilter which allows for topologically constrained evolution of the level set. Identical to the original functionality of the FastMarchingImageFilter, the evolution of the level set of a single or multiple genus zero, well-composed seed objects proceeds according to the specified parameters. With our proposed enhancements, the user can either choose to prevent the level set from merging with itself such that the original topology of the initial seed object(s) is not violated or that no handles are created during the evolution process. However, in contrast to earlier approaches which relied on the concept of the simple point implicitly requiring the definition of a user-specified foreground/background connectivity, we use the related, but more restrictive concept of well-composed sets to topologically constrain the evolution of the level set. Utility of our submission is demonstrated on both 2-D and 3-D brain images. Note that this submission is a companion piece to a more theoretical discussion of our work given in [9]
ITK-Based Implementation of Two-Projection 2D/3D Registration Method with an Application in Patient Setup for External Beam Radiotherapy
Authors: Wu Jian
Published: January 2022

This document describes an ITK-based implementation of intensity-based 2D/3D rigid image registration for patient setup assessment in external beam radiotherapy. The registration framework was designed to simultaneously register two projection images to a 3D image volume. The projection geometry was set up to simulate the x-ray imaging system that attached to a medical linear accelerator for cancer treatment. The normalized correlation was used as the similarity measure and the Powell’s optimizer was used as the optimization method. Siddon-Jacobs fast ray-tracing algorithm was implemented to compute projection images from a 3D image volume.
Anomalous Diffusion Paradigm for Image Denoising Process
Authors: Senra Filho Antonio Carlos da Silva , Murta junior Luiz otavio
Published: January 2022

Anisotropic and isotropic diffusion equations have been extensively applied on biomedical image processing for many years and a great diversity of algorithm have been proposed by the scientific community. Here, it is available a recent new implementation of the anomalous diffusion equation, based on the Fokker-Planck PDE diffusion equation (also known as the Porous Media equation). The major contribution of the anomalous process in the image processing area is the possibility to regulates a sub or super-diffusion characteristic in the noise attenuation problem, which have been showed as a suitable solution for the preservation of fine details in complex objects such as the human brain. An ITK Module is offered here in order to easily add the Anisotropic Anomalous Diffusion (AAD) and Isotropic Anomalous Diffusion (IAD) filters in the ITK hierarchy.
Efficient multithreading for manycore processor: Multidimensional domain decomposition using Intel® TBB
Authors: St-Onge Etienne , Scherrer Benoit , Warfield Simon
Published: January 2022

The Insight Toolkit (ITK) utilizes a generic design for image processing filters that allows many developers to rapidly implement new algorithms. While ITK filters benefit from a platform-independent and versatile multithreading capability, the current implementation does not easily achieve high performance. First, ITK relies on a static decomposition of the image into subsets of equal size which is highly inefficient when the computational complexity varies between subsets (unbalanced workloads). Second, the current domain decomposition is limited to subdivide the input domain along a single dimension (typically the slice dimension in a 3-D volume), which causes a multithreading under-utilization when the number of threads is larger than the size of this dimension when using massively parallel compute systems. We previously presented a new itk::TBBImageToImageFilter class that replaced the static task decomposition by a dynamic task decomposition for improved workload balancing, in which the job scheduling task was optimized using the Intel® Threading Building Blocks (TBB) library. In this work, we propose a new multidimensional dynamic image decomposition approach that allows decomposition over an arbitrary number of dimensions. This new generic multithreading capability, combined with the TBB dynamic task scheduler, substantially improves multithreading performance when using massively parallel processors.
Vessel Enhancing Diffusion Filter
Authors: Enquobahrie Andinet , Ibanez Luis , Bullitt Elizabeth , Aylward Stephen
Published: January 2022

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.
Smart Nearest Neighbors
Authors: Doria David , Zhu Wanlin
Published: January 2022

This document presents an implementation of two algorithms, Voronoi Neighbors and Binary Space Partition (BSP) Neighbors. These algorithms find neighbors of a point in a point set that are somehow better'' than aK nearest neighbors’’ or a ``all neighbors within a radius’’ query. This type of nearest neighbor query is more computationally expensive, but results in set of neighbors with more desirable properties. The BSP Neighbors search ensures that there is less local duplication, while the Voronoi Neighbors search ensures that the spatial arrangement of the neighbors is as uniform as possible.

These algorithms are explained in ``Point Primitives for Interactive Modeling and Processing of 3D Geometry’’.

The code is available here: https://github.com/daviddoria/SmartNearestNeighbors
STL file format MeshIO class for ITK
Authors: Ibanez Luis
Published: January 2022

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.
Non-negative matrix factorization framework for dimensionality reduction and unsupervised clustering
Authors: Pathak Sayan
Published: January 2022

Non-negative Matrix Factorization (NMF) is a robust approach to learning spatially localized parts-based subspace patterns in applications such as document analysis, image interpretation, and gene expression analysis. NMF-based decomposition capabilities are lacking in the present ITK toolkit. We provide a generic framework for such decompositions. A specific implementation using a Kulback-Liebler type divergence function is provided to illustrate a possible extension of the base class along with test images to illustrate usage. We have found this method to be robust to noisy image data and show examples from our on-going research using the Allan Brain Atlas data to illustrate its ability to analyze higher dimension data.
A program to cast and convert image files
Authors: Staring Marius , Klein Stefan
Published: January 2022

This program, based completely on ITK, converts between the different file types available in the ITK. Casting between the different pixel component types is available as an option. Currently, only scalar pixel types are supported.
ITK Order K Distance Transform
Authors: Lloyd Bryn , Warfield Simon
Published: January 2022

We have implemented an Order K Distance Transform filter. The Order K distance transform computes the distances to the k nearest foreground pixels. Additionally the Order K Voronoi diagram can be computed. This work was supported in part by R21 MH67054, NSF ITR 0426558 and P41 RR13218.
Level Set Segmentation: Active Contours without edge
Authors: Mosaliganti Kishore , Smith Benjamin , Gelas Arnaud , Gouaillard Alexandre , megason sean
Published: January 2022

An Insight Toolkit (ITK) processing framework for segmentation using active contours without edges is presented in this paper. Our algorithm is based on the work of Chan and Vese [1] that uses level- sets to accomplish region segmentation in images with poor or no gradient information. The basic idea is to partion the image into two piecewise constant intensity regions. This work is in contrast to the level-set methods currently available in ITK which necessarily require gradient information. Similar to those methods, the methods presented in this paper are also made efﬁcient using a sparse implementation strategy that solves the contour evolution PDE at the level-set boundary. The framework consists of 6 new ITK ﬁlters that inherit in succession from itk::SegmentationFilter. We include 2D/3D example code, parameter settings and show the results generated on a 2D cardiac image.
Automatic Conductance Estimation Methods for Anisotropic Diffusion ITK Filters
Authors: Senra Filho Antonio Carlos da Silva
Published: January 2022

The anisotropic diffusion algorithm has been intensively studied in the past decades, which could be considered as a very efficient image denoising procedure in many biomedical applications. Several authors contributed many clever solutions for diffusion parameters fitting in specific imaging modalities. Furthermore, besides improvements regarding the image denoising quality, one important variable that must be carefully set is the conductance, which regulates the structural edges preservation among the objects presented in the image. The conductance value is strongly dependent on image noise level and an appropriate parameter setting is, usually, difficult to find for different images databases and modalities. Fortunately, thanks to many efforts from the scientific community, a few automatic methods have been proposed in order to set the conductance value automatically. Here, it is presented an ITK class which offers a simple collection of the most common automatic conductance setting approaches in order to assist researchers in image denoising procedures using anisotropic-based filtering methods (such as well described in the AnisotropicDiffusionFunction class).
An ITK implementation of the Normalized Gradient Field Image to Image Metric
Authors: Wollny Gert , Ledesma-Carbayo María-Jesus , Santos Andrés
Published: January 2022

This article describes the ITK implementation of a Normalized Gradient Fields based image-to-image metric. Some properties of the metric are discussed and example registrations are presented.
ModulusImageFilter
Authors: Lehmann Gaetan
Published: January 2022

ModulusImageFilter is a simple image filter to compute the modulus (x % dividend) pixel-wise.
Inverting deformation fields using a fixed point iteration scheme
Authors: Luethi Marcel
Published: January 2022

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.
Rotational Registration of Spherical Surfaces Represented as QuadEdge Meshes
Authors: Ibanez Luis , Audette Michel , Yeo B.t. thomas , Golland Polina
Published: January 2022

This document describes a contribution to the Insight Toolkit intended to support the process of registering two Meshes. The methods included here are restricted to Meshes with a Spherical geometry and topology, and with scalar values associated to their nodes. 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.
2D/3D Multi-Modality Image Registration in Non-Destructive Evaluation
Authors: Jia Zhen
Published: January 2022

Non-destructive evaluation(NDE) is a group of analysis techniques used in industry to evaluate the property of a material, component or product without causing damage. Among all the techniques, radiology and thermography are two most common methods that are used to inspect the property of the interior of product and combining the knowledge contained in images of two modalites requires the space alignment. In this article, a 2D/3D multi-modality image registration scheme is presented to find the alignment between thermal infrared(IR) image and CT image of a engine blade.
Automated high-throughput registration for localizing 3D mouse brain gene expression using ITK
Authors: Ng Lydia , Hawrylycz Michael , Haynor David
Published: January 2022

The Allen Brain Atlas (ABA) project aims to create a cellular-resolution, genome-wide map of gene expression in the adult mouse brain. The resulting in situ hybridization (ISH) image data will be available free-of-charge to the public. Additionally, we are developing an informatics pipeline to support searching of the data by anatomic region and expression level and/or pattern. This paper describes a robust, high-throughput registration scheme to automatically annotate hierarchical brain structures in the ISH imagery.
Class for Serial Transformations
Authors: Rohlfing Torsten
Published: January 2022

This paper describes a simple class for serial transformations, i.e., the concatenation of other transformations. This can be used for .
Uniform B-Splines for the VTK Imaging Pipeline
Authors: Gobbi David , Starreveld Yves P.
Published: January 2022

Uniform B-splines are used widely in image processing because they provide maximal smoothness compared to any other piecewise polynomial of the same degree and support. This paper describes VTK classes for performing two functions: image interpolation via B-splines, and non-rigid coordinate transformation via B-splines. Special attention is paid to different boundary conditions for the ends of the spline: image interpolation supports clamped, mirrored, and repeated boundary conditions while B- spline grid transformations support clamped and zero-past-boundary conditions. The use of these classes for image deformation is demonstrated.
Open Source and Open Data for MICCAI - Announcement and Program
Authors: Aylward Stephen , Cleary Kevin , Ibanez Luis , Kapur Tina
Published: January 2022

This workshop features peer-reviewed submissions that describe the available data and software of MICCAI.
Cerebral Cortical Thickness Estimation using the TINA
Open-Source Image Analysis Environment
Authors: Scott Marietta , Bromiley Paul A. , Thacker Neil A.
Published: January 2022

This paper gives an overview of the use and development of the TINA open-source medical image analysis environment, with respect to the determination of human cerebral cortical thickness estimation from magnetic resonance images. The ultimate aim of TINA is to provide a validated system where the source code and datasets are freely available in order to allow peer-validation of published results.
Moore Neighbor Tracing
Authors: Doria David
Published: January 2022

This document presents an implementation of Moore Neighbor Tracing - an algorithm to find an ordered outline of a blob or contour in an image.

An excellent tutorial on Moore Neighbor Tracing is provided here: http://www.imageprocessingplace.com/downloads_V3/root_downloads/tutorials/contour_tracing_Abeer_George_Ghuneim/moore.html.

The code is available here: https://github.com/daviddoria/MooreTracing
WrapITK: Enhanced languages support for the Insight Toolkit
Authors: Lehmann Gaetan , Pincus Zachary , Regrain Benoit
Published: January 2022

ITK is a huge image analysis library, which contains lots of state of the arts algorithms implementations. However, using it in C++ can be difficult and is definitively bad suited for prototyping. WrapITK aims to allow classes from ITK (and custom, classes that interact with ITK) to be “wrapped” for use with languages like Python, Tcl, and Java.
ITK-based Registration of Large Images from Light Microscopy: A Biomedical Application
Authors: Mosaliganti Kishore , Pan Tony , machiraju raghu , Huang Kun , Saltz Joel
Published: January 2022

Inactivation of the retinoblastoma gene in mouse embryos results in morphological changes in the placenta, which has been shown to affect fetal survivability. The construction of a 3D virtual placenta aids in accurately quantifying structural changes using image analysis. The placenta dataset consisted of 786 images totaling 550 GB in size, which were registered into a volumetric dataset using ITK’s registration framework. The registration process faces many challenges arising from the large image sizes, damages during sectioning, staining gradients both within and across sections, and background noise leading to local solutions. In this work, we implement a rigorous ITK-based preprocessing pipeline for removing noise and employ a novel 2-level optimization strategy for enhanced registration in ITK. We provide 3D visualizations and numerical results to demonstrate our improvements.
Morphology with parabolic structuring elements
Authors: Beare Richard
Published: January 2022

Morphological erosion and dilation filters employ a structuring function, with flat structuring functions being the most common example. This article will use the term "parabolic", but much of the literature uses "quadratic" structuring functions are less well known but theoretically very important and practically very useful. This paper briefly introduces morphology using parabolic structuring functions, describes the ITK classes used to implement them and includes a number of sample applications.
Scene Graph: Visualization of Coordinate Systems in the Image Guided Surgical Toolkit
Authors: Dandibhotla Janakiram , Gary Kevin
Published: January 2022

In a surgical environment, there are many tools and objects (including the patient) being used. In a computer-aided surgery, the position of each of these tools in the operating room is very critical and generally will be tracked in their own coordinate systems. To show the surgeon a real time picture of the operating environment on a computer monitor, we need to know the position of each object with respect to one common coordinate system, which in turn can be achieved by knowing each coordinate system and the transforms between them. Image-Guided Surgical Toolkit is a software toolkit designed to enable biomedical researchers to rapidly prototype and create new applications for image-guided surgery. In IGSTK, in which the coordinate systems and the transforms are being successfully used, there is no central data structure or repository, which will hold all the coordinate systems and the transforms between them. Such a data structure could help the IGSTK software developers to have more confidence in the code they have written. This project develops a tool, which will create such a data structure and dynamically show the changes to it, to help such software developers to write better code.
itkMultipleUnlabeledImagesToLabeledImageFilter
Authors: Tamburo Robert
Published: January 2022

This document describes a filter called itkMultipleUnlabeledImagesToLabeledImageFilter, which takes multiple images as input and generates a single image of labeled pixels. Pixels to be labeled for each image are determined by an intensity threshold. Submitted with this document is the source code for the filter and source code for demonstrating filter usage via an image input as an argument. Also included is source code for testing the functionality of the filter.
GPU and CPU implementation of Young - Van Vliet's Recursive Gaussian Smoothing Filter
Authors: Vidal-Migallon Irina , Commowick Olivier , Pennec Xavier , Dauguet Julien , Vercauteren Tom
Published: January 2022

This document describes an implementation for GPU and CPU of Young and Van Vliet’s recursive Gaussian smoothing as an external module for the Insight Toolkit ITK, version 4.* www.itk.org. In the absence of an OpenCL-capable platform, the code will run the CPU implementation as an alternative to the existing Deriche recursive Gaussian smoothing filter in ITK.
An Open Source Framework for Surgical Simulation
Authors: Rodriguez-Florido Miguel Angel , Sanchez Escobar Norberto , Santana Raul , Ruiz-Alzola Juan
Published: January 2022

In this work a software framework for the virtual surgical simulation is presented. Our environment ESQUI (The acronym comes from the Spanish “Entorno para Simulacion QUIrurgica”, i.e. Framework for Surgical Simulation) is based on an open software and multi-platform architecture (Unix, Windows, etc.), resulting in a suitable framework for research and development. The modularity and connectivity between its components allow the environment to be extensible and adaptable to any type of virtual simulation. The virtual surgical scene is described by an XML file that contains all the necessary information for the simulation. This file description language has been named Surgical Reality Modeling Language (SRML). Although our framework is still under development and needs validation in education and clinical training, our environment ESQUI has proved to be a modular platform that runs across most important areas of virtual surgical simulation.
Real-Time Ultrasound Image Analysis for the Insight Toolkit
Authors: Wang David , Chang Wilson , Stetten George
Published: January 2022

We have successfully created a software environment in which ultrasound data can be manipulated by, ITK (the Insight Tool-Kit), in real-time. We were able to access each frame generated within the resident computer of a TerasonTM Ultrasound Machine, convert it into the ITK image format, and demonstrate the concurrent operation of ITK on the same computer by writing the images to an external hard drive. At a rate of 10 frames per second, 512 by 512 pixel grayscale frames were written by ITK methods to the external hard drive through USB 2.0 while the ultrasound scan was occurring without thrashing or delay in system performance. This simple exercise demonstrates the potential of ITK in processing ultrasound images in real-time in addition to the more traditional off-line processing.
Go-Go Gabor Gadgetry
Authors: Tustison Nicholas J. , Gee James
Published: January 2022

Although Gabor filtering is quite prevalent in the computer vision community for such tasks as texture segmentation and motion analysis, such capabilities are conspicuously absent from the Insight Toolkit. The contribution described in this paper attempts to remedy this deficiency by introducing two new classes: itkGaborKernelFunction and itkGaborImageSource.
Digital Topology
Authors: Lamy Julien
Published: January 2022

This documents describes a set of classes to integrate digital topology in the Insight Toolkit, with an application to homotopic thinning. The skeletonization filter implemented using our set of classes is twice as fast as BinaryThinningImageFilter and can be used on images of any dimension.
Walk In A Triangulation : Straight Walk
Authors: Rigaud Stephane , Gouaillard Alexandre
Published: January 2022

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.
Perturbing Mesh Vertices with Additive Gaussian Noise
Authors: Vigneault Davis
Published: January 2022

This brief document provides an introduction to an external ITK module, DVMeshNoise. This module provides classes for perturbing the positions of the vertices of either an itk::Mesh or itk::QuadEdgeMesh with Gaussian noise. This may be useful in testing the robustness of an algorithm to small changes in the input mesh, augmenting datasets for machine learning, and counteracting deleterious effects which highly regular regions of a mesh may occasionally have on mesh processing. After demonstrating basic usage, we present a practical example to show how these classes can be incorporated into a pipeline to improve mesh quality.
optimized image iterators
Authors: Zhu Wanlin
Published: January 2022

This document describes the iteration direction optimized Image Iterators . Comparing with the original corresponding iterators, the new iterators provide automatic iteration direction optimization and give more flexible. They are more efficient when the fastest moving direction has small size. The derived template class ImagePieceWiseLinearIteratorWithIndex is a generic class that can be replace the ImageLinearIterator and ImageSliceIterator. The paper present the implementation and examples of these classes. This paper is accompanied with the source code and experiments.
Implementation of local structure tensor and enhancement anisotropic diffusion filters in ITK
Authors: Enquobahrie Andinet , Yang Hua , Aylward Stephen
Published: January 2022

This paper describes implementation of local structure tensor and anisotropic enhancement diffusion filters using the Insight Toolkit. The anisotropic diffusion filters are implemented using ITK’s finite difference solver framework. The filters are used to implement the 3D edge-enhancing diffusion ( EED), coherence-enhancing diffusion (CED) and hybrid diffusion with continuous switch(HDCS) noise filtering algorithms described in Mendrik et al[1].

The most up-to-date version of the code presented in this paper is distributed with the TubeTK project: http://public.kitware.com/Wiki/TubeTK
Combining labeled images with ITK
Authors: Lehmann Gaetan
Published: January 2022

Combining some labeled images is a quite common and useful task in image analysis. That’s something we may want to do to prepare the markers for a watershed from markers for example, or to write the output of several segmentations in a single file. This article comes with three new filters to make the combination of labeled images easier with ITK. This contribution also try to provide an implementation better integrated with the ITK pipeline model than the itkMultipleUnlabeledImagesToLabeledImageFilter contribution.
InsightToolkit Kinetic Analysis (itk::ka) Library
Authors: Dowson Nicholas , Baker Charles , Raffelt David , Smith Jye , Thomas Paul , Salvado Olivier , Rose Stephen
Published: January 2022

This paper describes how to compile and use the Insight Toolkit Kinetic Analysis library (itk::ka), to perform analysis of dynamic medical images, along with a brief overview of the library source code. Supplied, are a set of interfaces to facilitate application development, application implementing a standard kinetic analysis pipeline (koala), and some sample data. Only versions of ITK4 and higher are currently supported.
Adaptive Moment Estimator (Adam) Optimizer in ITK v3
Authors: Ajani Bhavya , Bharadwaj Aditya
Published: January 2022

This document describes an ITK class implementing an Adaptive Moment Estimator (Adam) optimizer algorithm within the Insight Toolkit ITK www.itk.org. Adam is an adaptive gradient descent optimizer, which independently adaptively estimates the gradient descent step for each parameter, at each iteration, based on stored past gradients. The optimizer stores exponentially decaying averages of past gradients to estimate first moment (the mean) and the second moment (the variance) of the gradients to formulate update rule for present iteration. The Adam optimizer compares favorably to other adaptive learning-method algorithms, converges faster, and is robust to saddle point. 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.
Consolidated morphology
Authors: Lehmann Gaetan , Beare Richard
Published: January 2022

Grayscale dilation and erosion are basic transformations of mathematical morphology. Used together or with other transformations, they are very useful tools for image analysis. However, they can be very time consuming, especially with 3D images, and with large structuring elements. Several algorithms have been created to decrease the computation time, some of them with some limitations of shape of structuring element. We have implemented several algorithms, studied their performance in different conditions, and shown that all of them are more efficients than the others in certain conditions. We finally introduce a new structuring element class and a some meta filter designed to select the best algorithm depending on the image and the structuring element, and to smoothely integrate the different algorithms available in the toolkit.
Unsupervised Segmentation for Myofiber Counting in Immunofluorescent Microscopy Images
Authors: Urish Kenneth , August Jonas , Huard Johnny
Published: January 2022

The gold standard for measuring muscle regeneration in muscular dystrophy therapies is counting the number of dystrophin-positive muscle fibers on a cryostat muscle section immunostained for dystrophin. The standard process of manually counting a few thousand myofibers is tedious, time consuming, and limits quantitative analysis of a therapy success. We present an unsupervised method for segmenting and counting the number of myofibers on an immunofluorescent microscopy image. The key threshold selection problem is resolved by maximizing the number of sub-threshold connected components. Components significantly smaller than the known lower bound myofiber area, the only input parameter, are ignored to reduce noise. Validation on a series of images (n=63) revealed that our algorithm varied by less than 10% from manual counts in the relevant range of operation. The algorithm allows us to quantify three-dimensional dystrophin expression and design experiments that address a major limitation in muscular dystrophy therapies, the limited distribution of dystrophin after treatment. Further we have extended this method to segment and count objects in other immunofluorescent images. The method was quickly developed and tested using the Insight Toolkit (ITK), an open source C++ library for the development of image analysis software.
BRAINSDemonWarp: An Applicaton to Perform Demons Registration
Authors: Johnson Hans , Zhao Yongqiang
Published: January 2022

In this paper, a software application is introduced for image registration. BrainDemonsWarp is a com- mand line program using Thirion and diffeomorphic demons algorithms. The program takes in a template image and a target image along with other optional parameters and registers the template image onto the target image. The resultant deformation ﬁelds and metric values can be written to a ﬁle. The program uses the Insight Toolkit (www.ITK.org) for all the computations, and can operate on any of the image types supported by that library.
MINC2.0 IO Support for ITK
Authors: Baghdadi Leila
Published: January 2022

MINC2.0 IO support REVISED! This revision has direction cosines and various other issues addressed.
N4ITK: Nick's N3 ITK Implementation For MRI Bias Field Correction
Authors: Tustison Nicholas J. , Gee James
Published: January 2022

Several algorithms exist for correcting the nonuniform intensity in magnetic resonance images caused by field inhomogeneities. These algorithms constitute important preprocessing steps for subsequent image analysis tasks. One such algorithm, known as parametric bias field correction (PABIC), has already been implemented in ITK. Another popular algorithm is the nonuniform intensity normalization (N3) approach. A particularly salient advantage of this algorithm is that it does not require a prior tissue model for its application. In addition, the source code for N3 is publicly available at the McConnell Brain Imaging Centre (Montreal Neurological Institute, McGill University) which includes source code and the coordinating set of perl scripts. This submission describes an implementation of the N3 algorithm for the Insight Toolkit given as a single class, viz. itk::N3MRIBiasFieldCorrectionImageFilter. We tried to maintain minimal difference between the publicly available MNI N3 implementation and our ITK im- plementation. The only intentional variation is the substitution of an earlier contribution, i.e. the class itk::BSplineScatteredDataPointSetToImageFilter, for the originally proposed least-squares approach for B-spline fitting used to model the bias field. In addition, we include a more extensive modification to the original N3 algorithm found in the class itk::N4MRIBiasFieldCorrectionImageFilter. The latter algorithm employs a multi-resolution approach, similar to FFD image registration strategies, and has a slightly modified iterative update scheme.
MIPP: A Medical Image Processing Platform based on ITK, VTK and Eclipse RCP
Authors: Swoboda Roland , Zwettler Gerald , Pfeifer Franz , Backfrieder Werner
Published: January 2022

A novel platform for realizing software prototypes in the area of medical image processing, analysis and visualization is introduced: The "Medical Image Processing Platform" (MIPP). A novel feature is the combination of ITK/VTK with Java/Eclipse RCP, four potential technologies complementing each other. While ITK and VTK provide comprehensive functionality for image processing and visualization, Java and Eclipse RCP facilitate the development of a modern and rich application.

RCP offers everything for creating plug-in based software. The benefits of integrating ITK and VTK in such a modular architecture are reusability and extensibility. Functionality usually found in software for medical image processing and visualization (2D and 3D viewers, DICOM and application data management, etc.) is provided by the MIPP platform as plug-ins, can be easily reused by new applications and needn't be re-implemented. Developers can extend the platform's features by contributing new plug-ins and, again, make these available for others.

The paper describes the architecture of the MIPP platform and outlines its most important functionality. Finally, three clinical software systems implemented with MIPP are presented.