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3DV1EWNIX is a data-, machine., and applicationindependent software system, developed and maintained on an ongoing basis by the Medical Image Processing Group. It is aimed at serving the needs of biomedical visualization researchers as well as biomedical end users. 3DVIEWNIX is not designed around a fixed methodology or a set of methods packaged in a fixed fashion for a fixed application. Instead, we have identified and incorporated in 3DVIEWNIX a set of basic imaging transforms that are required in most visualization, manipulation, and analysis methods. The result is a powerful exploratory environment that provides not only the commonly used standard tools but also an immense variety of others. In addition to visualization, it incorporates a variety of multidimensional structure manipulation and analysis methods. We have tried to make its design as much as possible image.dimensionality-independent to make itjust as convenient to process 2D and 3D data as it is to process 4D data. It is based on UNIX, C, XWindow and our own mulddimensional generalization of the 2D ACR-NEMA standards for image data representation. It is distributed with source code in an open fashion. A single source code version is installed on a variety of computing platforms. It is currently in use worldwide.

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The relative performance of five fully 3D PET reconstruction algorithms is evaluated. The algorithms are a filtered backprojection (FBP) method and two variants each of the EM-ML and ART iterative methods. For each of the iterative methods, one variant makes use of voxels and the other makes use of 'blobs' (spherically symmetric functions smoothly decaying to zero at their boundaries) as basis functions in its discrete reconstruction model. The methods are evaluated from the point of view of the efficacy of the reconstructions produced by them for three typical medical tasks--estimation of the average activity inside specific regions of interest, detection of hot spots, and detection of cold spots. A free parameter is allowed in the description of each of the five algorithms; the parameters are determined by a training process during which a value of the free parameter is selected which (nearly) maximizes a technical figure of merit. Such training and the actual comparative evaluation is done by making use of randomly generated phantoms and their projection data. The methodology allows assignation of levels of statistical significance to claims of the relative superiority of one algorithm over another for a particular task. We find that using blobs as basis functions in the iterative algorithms is definitely advantageous over using voxels. This result has high statistical significance. (We also include a visual illustration of it.) Comparing FBP, EM-ML using blobs, and ART using blobs, we do not find a clear difference in the overall performance of the investigated variants of the methods. If anything, our results suggest that ART using blobs may be the most efficacious of the three.

We present a practical methodology for evaluating 3D PET reconstruction methods. It includes generation of random samples from a statistically described ensemble of 3D images resembling those to which PET would be applied in a medical situation, generation of corresponding projection data with noise and detector point spread function simulating those of a 3D PET scanner, assignment of figures of merit appropriate for the intended medical applications, optimization of the reconstruction algorithms on a training set of data, and statistical testing of the validity of hypotheses that say that two reconstruction algorithms perform equally well (from the point of view of a particular figure of merit) as compared to the alternative hypotheses that say that one of the algorithms outperforms the other. Although the methodology was developed with the 3D PET in mind, it can be used, with minor changes, for other 3D data collection methods, such as fully 3D cr or SPECT.

Objective: To investigate the relation between atrophy of the hippocampal region and brain functional patterns during episodic memory processing in Alzheimer's disease. Patients and methods: Whole brain structural magnetic resonance imaging (MRI) data and single photon emission computed tomography (SPECT) measures of regional cerebral blood flow (rCBF) were obtained during a verbal recognition memory task in nine subjects with mild Alzheimer's disease and 10 elderly healthy controls. Using the statistical parametric mapping approach, voxel based comparisons were made on the MRI data to identify clusters of significantly reduced grey matter concentrations in the hippocampal region in the Alzheimer patients relative to the controls. The mean grey matter density in the voxel cluster of greatest hippocampal atrophy was extracted for each Alzheimer subject. This measure was used to investigate, on a voxel by voxel basis, the presence of significant correlations between the degree of hippocampal atrophy and the rCBF SPECT measures obtained during the memory task. Results: Direct correlations were detected between the hippocampal grey matter density and rCBF values in voxel clusters located bilaterally in the temporal neocortex, in the left medial temporal region, and in the left posterior cingulate cortex during the memory task in the Alzheimer's disease group (p < 0.001). Conversely, measures of hippocampal atrophy were negatively correlated with rCBF values in voxel clusters located in the frontal lobes, involving the right and left inferior frontal gyri and the insula (p < 0.001). Conclusions: Hippocampal atrophic changes in Alzheimer's disease are associated with reduced functional activity in limbic and associative temporal regions during episodic memory processing, but with increased activity in frontal areas, possibly on a compensatory basis.

The design of proper models for authorization and access control for electronic patient record (EPR) is essential to a wide scale use of EPR in large health organizations. In this paper, we propose a contextual role-based access control authorization model aiming to increase the patient privacy and the confidentiality of patient data, whereas being flexible enough to consider specific cases. This model regulates user's access to EPR based on organizational roles. It supports a role-tree hierarchy with authorization inheritance; positive and negative authorizations; static and dynamic separation of duties based on weak and strong role conflicts. Contextual authorizations use environmental information available at access time, like user/patient relationship, in order to decide whether a user is allowed to access an EPR resource. This enables the specification of a more flexible and precise authorization policy, where permission is granted or denied according to the right and the need of the user to carry out a particular job function.