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.

Cerebral Cortical Thickness Estimation using the TINA
 Open-Source Image Analysis Environment

This paper focuses on the role of open-source software in the development of a novel magnetic resonance image (MRI) tissue classification algorithm. Specifically, we describe the of use existing classes in the Insight Segmentation and Registration Toolkit (ITK) and several new classes that were implemented to perform non-parametric density estimation and entropy minimization. These new classes also provide a general framework for nonparametric density estimation and related applications.

A nonparametric, entropy-minimizing MRI tissue classification algorithm implementation using ITK

In this paper , we propose an extension to the National Library of Medicine's Insight Segmentation and Registration Toolkit (ITK. www.itk.org) with a companion image access and archival system that merges the image transfer capabilities of DICOM with DSpace (www.dspace.org), an open-source web-based digital library technology. We have extended and linked existing, freely-available DICOM and digital library software to create DICOM Accessible Digital Libraries (DADLs). Specifically, DICOM objects (and other medical image data formats such at Analyze,MetaImage) uploaded to a DADL can be grouped with other files such as journal articles or tracker data, viewed as thumbnails, and made publicly or privately available for others to search and download from a linked DICOM server. In that manner, once a researcher has identified the data he / she needs via an Internet search using meaningful descriptors, the data can be directly downloaded via standard DICOM query and retrieve utilities and that data will be perpetually indexed and accessible via an Internet handle.

A DICOM-based Software Infrastructure for Data Archiving

The Image-Guided Surgery Toolkit (IGSTK) is an Open Source software project being developed under NIH/NIBIB funding. The toolkit will provide a common platform for implementing image-guided surgery applications and for fostering research in the field. The toolkit is based on several other open source toolkits including ITK, VTK and FLTK. Its architecture is based on the use of medium size classes, each one of them containing an explicit State Machine and a minimized API that enforces fault tolerance by design. This paper describes the architecture and its rationale.

IGSTK: A State Machine Architecture for an Open Source Software Toolkit for Image-Guided Surgery Applications

Mathematical models are often used to describe natural phenomena, organisms and anatomy. This paper presents a Model-Image Registration framework that can be used to evaluate models of anatomical shape. An optimisation process is applied to the model parameters to fit the model to an organ of interest in a volumetric image. The fit is obtained by maximising a metric that measures how closely the model surface atches the image edge features, according to gradient magnitude and orientation with respect to the surface normal. The system was tested using a spiral shell model, with generated data as ground truth, and also with CT scans of the temporal bone. The parameters converge to within a close tolerance after a few hundred iterations on the test data, and show promising results on registering with the clinical data.

Model-Image Registration of Parametric Shape Models: Fitting a Shell to the Cochlea

We propose a novel framework at MICCAI 2005 to predict pacing sites in the left ventricle (LV) of a heart. This framework can be used to assist pacemaker implantation and programming in cardiac resynchronization therapy (CRT) that is a widely adopted therapy for heart failure patients. Hierarchical agglomerative clustering technique is performed to the time series of LV wall thickness to identify pacing site candidates. Meanwhile, pearson correlation coefficients of wall motion series show the dissimilarity between them. These main components of our clustering based prediction framework are implemented by using open source software toolkit PRTools.

Clustering Based Cardiac Resynchronization Therapy Prediction using Open Source Toolkit PRTools

We describe the open source implementation of an adaptive tetrahedral mesh generator particularly targeted for non-rigid FEM registration of MR images. While many medical imaging applications require robust mesh generation, there are few codes available. Moreover, most of the practical implementations are commercial. The algorithm we have implemented has been previously evaluated for simulations of highly deformable objects, and the preliminary results show its applicability to the targeted application. The implementation we describe is open source and will be available within Insight Toolkit.

Tetrahedral mesh generation for medical imaging

BioImage Suite is an integrated image analysis software suite
developed at Yale. It uses a combination of C++ and Tcl in the same
fashion as that pioneered by the Visualization Toolkit (VTK) and it
leverages both VTK and the Insight Toolkit. It has extensive capabilities
for both neuro/cardiac and abdominal image analysis and state of the
art visualization. It is currently in use at Yale; a first public release is
expected before the end of 2005.

BioImage Suite: An integrated medical image analysis suite

Camino is an open-source, object-oriented software package for processing diffusion MRI data. Camino implements a data processing pipeline, which allows for easy scripting and flexible integration with other software. This paper summarises the features of Camino at each stage of the pipeline from the raw data to the statistics used by clinicians and researchers. The paper also discusses the role of Camino in the paper "An Automated Approach to Connectivity-based Partitioning of Brain Structures", published at MICCAI 2005.

Camino: Diffusion MRI reconstruction and processing

A hierarchy of path data types and basic path filters were added to ITK, providing a general framework for curves that map a scalar value to a point in n-dimensional space. The framework supports curves that are either continuous (parametric curves) or discrete (chain-codes). Example usage of the entire framework is demonstrated using a previously published 2D active contour algorithm that was converted to ITK.