This document describes an open source, high performance ultrasound B-Mode implementation based on the Insight Toolkit (ITK). ITK extensions are presented to calculate the radio-frequency (RF) signal envelope. A variety of 1D Fast Fourier Transform options are introduced including VNL, FFTW, and an OpenCL solution. Scan conversion is implemented for phased array or curvilinear transducers. The entire image processing pipeline is streamable to limit memory consumption during multi-frame or 3D acquisitions with the introduction of an itk::StreamingResampleImageFilter.


An Open Source, Fast Ultrasound B-Mode Implementation for Commodity Hardware

Segmentation forms the onset for image analysis especially for medical images, making any abnormalities in tissues distinctly visible. Possible application includes the detection of tumor boundary in SPECT, MRI or electron MRI (EMRI). Nevertheless, tumors being heterogeneous pose a great problem when automatic segmentation is attempted to accurately detect the region of interest (ROI). Consequently, it is a challenging task to design an automatic segmentation algorithm without the incorporation of 'a priori' knowledge of an organ being imaged. To meet this challenge, here we propose an intelligence-based approach integrating evolutionary k-means algorithm within multi-resolution framework for feature segmentation with higher accuracy and lower user interaction cost. The approach provides several advantages. First, spherical coordinate transform (SCT) is applied on original RGB data for the identification of variegated coloring as well as for significant computational overhead reduction. Second the translation invariant property of the discrete wavelet frames (DWF) is exploited to define the features, color and texture using chromaticity of LL band and luminance of LH and HL band respectively. Finally, the genetic algorithm based K-means (GKA), which has the ability to learn intelligently the distribution of different tissue types without any prior knowledge, is adopted to cluster the feature space with optimized cluster centers. 
Experimental results of proposed algorithm using multi-modality images such as MRI, SPECT, and EMRI are presented and analyzed in terms of error measures to verify its effectiveness and feasibility for medical applications.

An Intelligent cluster-based segmentation using Wavelet Features:Application to Medical Images

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.

A Mesh Front Iterator for VTK

Region growing is a technique that can be used to propagate information over a mesh. In a previous submission, "A Mesh Front Iterator for VTK", we introduced an iterator that can be used with vtkPointSet subclasses to traverse a mesh. It is sometimes useful to visit only vertices that are "similar" to their neighbors by some definition. This concept can be used to select many types of common regions, including planar regions or regions with similar color, to name a few. In this paper, we propose an iterator which propagates on a mesh using a condition test which can be easily modified.

The latest code is available here: https://github.com/daviddoria/MeshConditionalFrontIterator

A Conditional Mesh Front Iterator for VTK

This document describes an implementation of a filter to perform Boolean operations between surfaces. The filter requires the GNU Triangulated Surface Library GTS to perform the operations. This document is accompanied with the source code, and the xml files necessary to create a paraview plugin.

Boolean Operations on Surfaces for VTK

The image registration framework in the Insight Tookit offers a powerful body of code for finding the optimal spatial transform that registers one image with another. However, ITK currently lacks a way to fit parametric models of image pixel values to an input image. This document describes new classes that enable use of the registration framework to provide this capability. We describe a new base class, itk::ParametricImageSource, that defines an interface for parametric image sources. An adapter class itk::ImageToParametricImageSourceMetric that enables itk::ParametricImageSources to be hooked into the registration framework is also described. An example adapter class that enables the existing itk::GaussianImageSource to be used for image fitting is presented, and we demonstrate use of the classes by fitting a 2D Gaussian function to an image generated by the itk::GaussianImageSource class.

Adapting the ITK Registration Framework to Fit Parametric Image Models

Tiff images are widely used and domain and instrument specific
information is often included in some tags. There isn't any standard
way of making use of this information in ITK at present. This article
introduces some minor additions to the ITK tiff reader to include the
content of some potentially useful tags in the image
MetaDataDictionary, thus enabling domain specific information to be
extracted from the tags within an ITK application.


Including TIFF tags in the MetaDataDictionary

This paper describes our contribution of three new classes to the Insight Toolkit community. We present a new ImageIO base class for streaming image file, along with two derived ImageIO classes for the VTK and the MRC file formats.

A Streaming IO Base Class and Support for Streaming the MRC and VTK File Format

Ultrasound is a very useful and convenient modality in medical imaging, due to its relatively small footprint, high resolution, negligible adverse effects, and real-time imaging capability -- in spite of its well-known artifacts. However, it is fairly difficult to fully benefit from its resolution and speed in advanced imaging research because of the closed nature of most ultrasound systems.

We propose a modular and extensible open-source toolkit MUSiiC S/W for rapid development and system setup for ultrasound research. Aimed at algorithm and experimental system builders as well as at clinical research, it allows standardized access to various types of ultrasound-derived real-time data streams, incorporates various tracking facilities, volume reconstruction, and connections to external software tools. By providing well-defined open standard interfaces between those building blocks, we aim at easy extensibility for third-party researchers.

The MUSiiC Toolkit: Modular Real-Time Toolkit for Advanced Ultrasound Research

The Surgical Assistant Workstation (SAW) provides a modular, open-source software framework to support rapid prototyping of computer-assisted surgery systems, especially those that benefit from enhanced 3D visualization and user interaction. The framework includes a library of components that can be used to implement master-slave or collaborative robot control systems with support for complex video
pipelines and a novel interactive surgical visualization environment. SAW includes standardized interface definitions (e.g., command names and payloads), with the goal of making the framework easily extensible so that developers can add support for their own robotic devices and associated hardware platforms. This paper presents an overview of the component-based architecture, followed by applications (use cases) in
the areas of minimally-invasive surgery (MIS), microsurgery, and surgical skill assessment.