Jeroen G. Snel

Quantitative in vivo analysis of the kinematics of carpal bones from three‐dimensional CT images using a deformable surface model and a three‐dimensional matching technique

The purpose of this study was to obtain quantitative information of the relative displacements and rotations of the carpal bones during movement of the wrist. Axial helical CT scans were made of the wrists of 11 volunteers. The wrists were imaged in the neutral position with a conventional CT technique, and in 15-20 other postures (flexion-extension, radial-ulnar deviation) with a low-dose technique. A segmentation of the carpal bones was obtained by applying a deformable surface model to the regular-dose scan. Next, each carpal bone, the radius, and ulna in this scan was registered with the corresponding bone in each low-dose scan using a three-dimensional matching technique. A detailed definition of the surfaces of the carpal bones was obtained from the regular-dose scans. The low-dose scans provided sufficient information to obtain an accurate match of each carpal bone with its counterpart in the regular-dose scan. Accurate estimates of the relative positions and orientations of the carpal bones during flexion and deviation were obtained. This quantification will be especially useful when monitoring changes in kinematics before and after operative interventions, like mini-arthrodeses. This technique can also be applied in the quantification of the movement of other bones in the body (e.g., ankle and cortical spine).

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 methods 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

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.

Detection of the carpal bone contours from 3-D MR images of the wrist using a planar radial scale-space snake

In this paper the authors consider the problems encountered when applying snake models to detect the contours of the carpal bones in 3-D MR images of the wrist. In order to improve the performance of the original snake model introduced by M. Kass et al. (1988), the authors propose a new image force based on one-dimensional (1-D) second-order Gaussian filtering and contrast equalization. The improved snake is less sensitive to model initialization and has no tendency to cut off contour sections of high curvature, because 1-D radial scale-space relaxation is used. Contour orientation is used to minimize the influence of neighboring image structures. Due to 1-D contrast equalization an intensity insensitive measure of external energy is obtained. As a consequence a good balance between internal and external energetic contributions of the snake is established, which also improves convergence. By incorporating this new image force into the snake model, the authors succeed in accurate contour detection, even when relatively high noise levels are present and when the contrast varies along the contours of the bones.

A Distributed Workflow Management System for Automated Medical Image Analysis and Logistics

Advances in medical image analysis have increased the need to integrate and deploy image analysis software in daily clinical routine and in epidemiological studies. We developed a distributed workflow management system (DWMS) that supports a wide portfolio of image analyses in different CT and MRI application domains. The DWMS supports software components for image import/export, caching, processing and notification that are distributed on a heterogeneous grid of commodity computers. Communication between the components is performed by exchanging SOAP messages on request of standard compliant Web services. The workflows are executed fully automatically upon receipt of the medical images. After processing, the results are routed to a workstation for review and further analysis or to an image archive (PACS). A Web-based monitor shows the status of running, pending and terminated workflows. The DWMS improves the interoperability between image acquisition devices, clinicians and researchers by making image analysis applications available in a transparent way, which accelerates the uptake of new research techniques. Through distributed computing, the workload is balanced and results can be obtained quicker. As the availability is guaranteed at a 24/7-hour basis, the system provides a reliable and completely automated solution for demanding image analysis tasks in a multi-vendor environment

Problem Solving Environment for Medical Image Analysis

The development of Medical Image Analysis (MIA) applications that can successfully be applied in clinical practice is difficult for several reasons, one of them being the large amount and variety of resources involved (people, data, methods, computing). The application goes through several phases (development, parameter optimization, evaluation and clinical deployment) usually supported by different systems. The lack of support for information flow from phase to phase puts extra logistics burden on the lifecycle of MIA applications. In this paper we describe our first efforts to develop a Problem Solving Environment (PSE) for MIA applications using the three systems available at the proof-of-concept environment of the Virtual Laboratory for e-Sciences project. The proposed PSE implements data provenance mechanisms that support information flow among systems, facilitating navigation across phases of the application lifecycle.