Integrated support for medical image analysis methods: from development to clinical application.

Computer-aided image analysis is becoming increasingly important to efficiently and safely handle large amounts of high-resolution images generated by advanced medical imaging devices. The development of medical image analysis (MIA) software with the required properties for clinical application, however, is difficult and labor-intensive. Such development should be supported by systems providing scalable computational capacity and storage space, as well as information management facilities. This paper describes the properties of distributed systems to support and facilitate the development, evaluation, and clinical application of MIA methods. First, the main characteristics of existing systems are presented. Then, the phases in a method's lifecycle are analyzed (development, parameter optimization, evaluation, clinical routine), identifying the types of users, tasks, and related computational issues. A scenario is described where all tasks are performed with the aid of computational tools integrated into an ideal supporting environment. The requirements for this environment are described, proposing a grid-oriented paradigm that emphasizes virtual collaboration among users, pieces of software, and devices distributed among geographically dispersed healthcare, research, and development enterprises. Finally, the characteristics of the existing systems are analyzed according to these requirements. The proposed requirements offer a useful framework to evaluate, compare, and improve the existing systems that support MIA development.

Towards a virtual laboratory for FMRI data management and analysis.

Functional Magnetic Resonance Imaging (fMRI) is a popular tool used in neuroscience research to study brain activation due to motor or cognitive stimulation. In fMRI studies, large amounts of data are acquired, processed, compared, annotated, shared by many users and archived for future reference. As such, fMRI studies have characteristics of applications that can benefit from grid computation approaches, in which users associated with virtual organizations can share high performance and large capacity computational resources. In the Virtual Laboratory for e-Science (VL-e) Project, initial steps have been taken to build a grid-enabled infrastructure to facilitate data management and analysis for fMRI. This article presents our current efforts for the construction of this infrastructure. We start with a brief overview of fMRI, and proceed with an analysis of the existing problems from a data management perspective. A description of the proposed infrastructure is presented, and the current status of the implementation is described with a few preliminary conclusions.

Deformable triangular surfaces using fast 1-D radial Lagrangian dynamics--segmentation of 3-D MR and CT images of the wrist.

We developed a new triangulated deformable surface model, which is used to detect the boundary of the bones in three-dimensional magnetic resonance (MR) and computed tomography (CT) images of the wrist. This surface model is robust to initialization and provides wide geometrical coverage and quantitative power. The surface is deformed by applying one-dimensional (1-D) radial Lagrangian dynamics. For initialization a tetrahedron is placed within the bone to be segmented. This initial surface is inflated to a binary approximation of the boundary. During inflation, the surface is refined by the addition of vertices. After the surface is fully inflated, a detailed, accurate boundary detection is obtained by the application of radial scale-space relaxation. In this optimization stage, the image intensity is filtered with a series of 1-D second-order Gaussian filters. The resolution of the triangulated mesh is adapted to the width of the Gaussian filter. To maintain the coherence between the vertices, a resampling technique is applied which is based on collapsing and splitting of edges. We regularized the triangulated mesh by a combination of volume-preserving vertex averaging and equi-angulation of edges. In this paper, we present both qualitative and quantitative results of the surface segmentations in eight MR and ten CT images.

Scaphoid kinematics in vivo.

The purpose of this study was to quantify 3-dimensional (3-D) in vivo scaphoid kinematics during flexion-extension motion (FEM) and radial-ulnar deviation (RUD) of the hand. The right wrists of 11 healthy volunteers were imaged by spiral computed tomography during RUD and 5 of those wrists also during FEM. With a matching technique, relative translations and rotations of the scaphoids were traced. Our results showed a broad spectrum of kinematic patterns of the scaphoid during RUD, with small intercarpal motions within the proximal carpal row. Some scaphoids rotated basically around the flexion-extension axis only whereas others rotated almost entirely around the deviation axis during RUD. During FEM we found highly uniform scaphoid motion patterns with large intercarpal motions within the proximal carpal row. These findings suggest that current theories cannot sufficiently explain wrist kinematics and stress the need for more in vivo studies on 3-D carpal kinematics.

In vivo analysis of carpal kinematics and comparative review of the literature.

PURPOSE: Techniques have been developed very recently with which it is possible to quantify accurately in vivo 3-dimensional (3-D) carpal kinematics. The aim of this study was to evaluate the feasibility of our novel 3-D registration technique by comparing our data with data found in the literature. METHOD: The right wrists of 11 healthy volunteers were imaged by spiral computed tomography (CT) during radial-ulnar deviation and 5 of those wrists were imaged also during flexion-extension motion. With a matching technique relative translations and rotations of the carpal bones were traced. We compared our in vivo results with data presented in the literature. RESULTS: We found our in vivo data largely to concur with in vitro data presented in the literature. In vivo studies revealed only larger out-of-plane motions within the proximal carpal row than described in most in vitro studies. In vivo studies also showed larger interindividual variations. CONCLUSIONS: A single functional model of carpal kinematics could not be determined. We expect that in vivo 3-D CT studies on carpal kinematics, especially when applied to dynamic wrist motion, will have future diagnostic applications and provide information on long-term results of surgical interventions.