OBJECTIVES: Many groups are developing computer-interpretable clinical guidelines (CIGs) for use during clinical encounters. CIGs use "Task-Network Models" for representation but differ in their approaches to addressing particular modeling challenges. We have studied similarities and differences between CIGs in order to identify issues that must be resolved before a consensus on a set of common components can be developed. DESIGN: We compared six models: Asbru, EON, GLIF, GUIDE, PRODIGY, and PROforma. Collaborators from groups that created these models represented, in their own formalisms, portions of two guidelines: American College of Chest Physicians cough guidelines [correction] and the Sixth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. MEASUREMENTS: We compared the models according to eight components that capture the structure of CIGs. The components enable modelers to encode guidelines as plans that organize decision and action tasks in networks. They also enable the encoded guidelines to be linked with patient data-a key requirement for enabling patient-specific decision support. RESULTS: We found consensus on many components, including plan organization, expression language, conceptual medical record model, medical concept model, and data abstractions. Differences were most apparent in underlying decision models, goal representation, use of scenarios, and structured medical actions. CONCLUSION: We identified guideline components that the CIG community could adopt as standards. Some of the participants are pursuing standardization of these components under the auspices of HL7.

We introduce a new approach for the solution of three interrelated problems: image registration, mosaicing and camera calibration. First we use well known similarity measures with particular interest in enhancing the performance for image registration. After initial registration we use a camera model to refine the alignment updating estimated camera parameters. A relaxation method applied on this model automatically estimates the lens parameters and uses them to eliminate the perspective and lens distortion observed in the overlap area of two images. Image mosaics are constructed by combining corrected images blending the border that contains pixels with optimally low total absolute difference in different spatial frequencies resulting in seamless mosaic images.

Mosaicing of images is the task of fusing a collection of images with smaller fields of view to obtain an image with a larger field of view. In order to accomplish this task, images should be geometrically and radiometrically corrected. We propose a new approach for perspective correction, useful when smaller images are gathered by rotating a camera with a fixed position. These images are projected onto a Gaussian sphere centered at the focal point of the camera which is later flattened on a plane tangent to the sphere. Using this procedure a field of view of up to 360/spl deg/ can be obtained on a mosaic image. We illustrate the geometric correction capability of our procedure (including more traditional gray level modification and seam elimination techniques) on outdoor scene images that partly overlap with each other.

An important issue in 3D image processing is the identification of points (voxels) which could be altered while leaving the topology unchanged-such points are referred to as simple points. We need time-efficient algorithms for identifying such points, since such computations are typically evoked over many iterations on large 3D images. We report new very fast algorithms for computing functions which identify 3D simple points and related topological conditions using "table-based" approaches which use a hierarchy of small tables of pointers. We also demonstrate time-storage tradeoffs which can be achieved by mixing table-based algorithms with more traditional techniques.

Reduction-augmentation operators change binary images by taking certain foreground pixels to the background (reduction) and certain background pixels to the foreground (augmentation). New connectivity preservation tests have been developed for special classes of parallel 2D reduction-augmentation operators. These special classes place requirements on the operators that are typical of those which appear in existing reduction-augmentation algorithms.

A new class of interconnection networks is presented for interconnecting the processors of general purpose massively parallel computers. This new class of interconnection networks, recursively connected networks (RCN), is constructed by methodically connecting together a number of basic networks, referred to as atoms, through the recursive application of a complete graph compound. A specific instance of this class, RCN-CUBE, where the basic atom is a binary hypercube, is shown to have desirable network properties such as small diameter, small degree, high bandwidth and optimal connectivity; and these compare favorably to those of other related networks. Convenient routing strategies are derived for the RCN class, which require only local information to route messages between nodes whenever routing within the basic atom requires only local information. RCN is shown to emulate the binary hypercube well under any permutation when the basic atom performs a binary hypercube emulation well; and RCN-CUBE can emulate the binary hypercube with only a small multiplicative factor increase in time performance. The time performance of RCN on various fundamental data movement operations frequently used in the design of parallel algorithms is analyzed and evaluated as a function of the performance on the basic atom used, and RCN-CUBE performance is shown to be very close to that required by the binary hypercube.

To efficiently use wavelet transforms in parallel mesh architectures, it is necessary to identify efficient embeddings of wavelet transform coefficients into such meshes. Two forms of 2D wavelet transform embedding into 2D meshes (with and without reconfigurability) are considered, and time performances for these embeddings over classes of image processing algorithms are compared. This demonstrates the superiority of one of these embeddings.>

Requirements for the support size and shape are investigated for the class of all adequate fully parallel thinning operators. Eleven pixel supports are shown to be the smallest possible supports, and the possible positions of the support pixels are shown to be well constrained. Constraints on support positions are demonstrated for operators with supports that are larger than optimal, and a sufficient test for connectivity preservation is reviewed. These results allow algorithm designers looking for small support operators to focus on a relatively small set of acceptable supports.>

The parallel shrinking of 3D binary images to single point residues is addressed using two subfields notions (A subfield is a partition of the image space into two disjoint subsets). Sufficient conditions for connectivity preservation are developed and convergence issues are discussed. An example two subfields algorithm is illustrated and evaluated.>

This correspondence defines approaches for the efficient generation of a spiral-like search pattern within bounded rectangularly tessellated regions. The defined spiral-like search pattern grows outward from a given source in a two-dimensional space, thus tending to minimize search time in many sequential tracking tasks. Efficient spiral generation is achieved by minimizing the number of operations required for interaction with boundaries. Algorithms are developed for both rectangular search regions and for arbitrary convex search regions.