625918
Part-Based Local Shape Models for Colon Polyp Detection
This paper presents a model-based technique for lesion detection in colon CT scans that uses analytical shape models to map the local shape curvature at individual voxels to anatomical labels. Local intensity profiles and curvature information have been previously used for discriminating between simple geometric shapes such as spherical and cylindrical structures. This paper introduces novel analytical shape models for colon-specific anatomy, viz. folds and polyps, built by combining parts with simpler geometric shapes. The models better approximate the actual shapes of relevant anatomical structures while allowing the application of model-based analysis on the simpler model parts. All parameters are derived from the analytical models, resulting in a simple voxel labeling scheme for classifying individual voxels in a CT volume. The algorithm's performance is evaluated against expert-determined ground truth on a database of 42 scans and performance is quantified by free-response receiver-operator curves.
6639595
An Uncertainty-Driven Hybrid of Intensity-Based and Feature-Based Registration with Application to Retinal and Lung CT Images
A new hybrid of feature-based and intensity-based registration is presented. The algorithm reflects a new understanding of the role of alignment error in the generation of registration constraints. This leads to an iterative process where distinctive image locations from the moving image are matched against the intensity structure of the fixed image. The search range of this matching process is controlled by both the uncertainty in the current transformation estimate and the properties of the image locations to be matched. The resulting hybrid algorithm is applied to retinal image registration by incorporating it as the main estimation engine within our recently published Dual-Bootstrap ICP algorithm. The hybrid algorithm is used to align serial and 4d CT images of the lung using a B-spline based deformation model.
5961676
Total Data Quality Management: The Case of IRI
Abstract Implementing a Total Data Quality Management (TDQM) program is not a trivial undertaking. Two key steps are (1) to clearly define what an organization means by data quality and (2) to develop metrics that measure data quality dimensions and that are linked to the organization’s goals and objectives. This paper presents the case of Information Resources, Inc., which exemplifies how a company can develop a viable TDQM program.
206570547
Performance evaluation of dynamic signature file methods
With rapid increase of information requirements from various application areas, there has been much research on dynamic information storage structures that effectively support insertions, deletions and updates. We evaluate the performance of the existing dynamic signature file methods such as the S-tree, Quid Filter and HS file, and provide guidelines for the most effective usage to a given operational environment. We derive analytic performance evaluation models of the storage structures based on retrieval time, storage overhead and insertion time. We also perform extensive experiments with various data distributions such as uniform, normal and exponential distributions.
9799056
Fitting via alternative random-effect models
When there are two alternative random-effect models leading to the same marginal model, inferences from one model can be used for the other model. We illustrate how a likelihood method for fitting models with independent random effects can be applied to seemingly very different models with correlated random effects. We also discuss some merits of using these alternative models.
40047629
Error Detection Process - Model, Design, and Its Impact on Computer Performance
Conventionally, reliability analyses either assume that a fault/error is detected immediately as it occurs, or ignore damage caused by imperfect detection mechanisms and error latency, namely, the time interval between the occurrence of an error and the detection of that error.
10094158
System and software designs for transaction processing in asymmetric communication environments
Observing that it is impractical to use traditional methods to control concurrency in broadcast-based asymmetric communication environments, we introduce a concurrency control protocol designed for broadcast-based transaction processing called Server Timestamp and Update Broadcast Supported Concurrency (STUBcast). STUBcast supports two new correctness criteria proposed in this paper—Single Serializability and Local Serializability. These criteria are weaker than global serializability, but are practical and easier to achieve in broadcast environments. This article also discusses the software design for the simulation program and the protocol implementation. Simulation results collected using our simulation program suggest that STUBcast could be very efficient in realistic application environments. Copyright © 2003 John Wiley & Sons, Ltd.