Interpretation time of serial chest CT examinations with stacked-metaphor workstation versus film alternator

PURPOSE: Interpretation time of serial staging chest CT cases, which each contained current and previous examinations, with a simple prototype workstation called filmstack was experimentally compared with interpretation time with a film alternator. MATERIALS AND METHODS: The filmstack displayed a "stack" of sections for each examination; user controls allowed rapid selection of preset attenuation windows and both synchronized and unsynchronized scrolling. Eight radiologists were timed as they used the filmstack and the film alternator to interpret four ergonomically complex serial CT cases. RESULTS: All reports dictated on the basis of findings with filmstack and film were of acceptable clinical accuracy. The time to examine a case with filmstack was significantly faster than the time with film, including the time to load and unload the alternator (99% confidence [P = .01]). There was no statistically significant difference in interpretation time between filmstack and prehung film. CONCLUSION: Use of a low-cost stacked CT workstation with a single 1,024 x 1,024 monitor is an effective means of interpreting cases that require comparison of multiple CT examinations.     

Low-contrast lesion segmentation in advanced MRI experiments by time-domain Ricker-type wavelets and fuzzy 2-means

Automated suspicious region segmentation has become a crucial need for the experts dealing with numerous images containing contrast-based lesions in MRI. Not all solutions, however, are based on mathematical infrastructure or providing adequate flexibility. On the other hand, segmentation of low-contrast lesions is very challenging for researchers; therefore, advanced magnetic resonance imaging (MRI) experiments are not commonly used in researches. Given the need of repeatability and adaptability, we present an automated framework for intelligent segmentation of brain lesions by wavelet imaging and fuzzy 2-means. Besides the general use of the wavelets in image processing, which is edge detection; we employed the second-order Ricker-type wavelets as the core of our novel imaging framework for low-contrast lesion segmentation. We firstly introduced the mathematical basis of several Ricker wavelet functions, which are in symmetrical form satisfying finite-energy and admissibility conditions of mother wavelets. Afterwards, we investigated three types of Ricker wavelets to apply on our clinical dataset containing susceptibility-weighted (SW) and minimum intensity projection SW (mIP-SW) images with barely-visible lesions. Finally, we adjusted the system parameters of the wavelets for optimization and post-segmentation by fuzzy 2-means. According to the preliminary results of the clinical experiments we conducted, our framework provided 93.53% average dice score (DSC) for SWI by Ricker-3 and 92.56% for mIP-SWI by Ricker-2 wavelet, as the main performance criteria of segmentation. Despite the lack of SWI or mIP-SWI experiments in the public datasets, we tested our framework with BraTS 2012 training sets containing real images with visible lesions and achieved an average of 88.13% DSC with 11.66% standard deviation by re-optimized framework for whole lesion segmentation, which is one of the highest among other relevant researches. In detail, 87.52% DSC for LG datasets with 11.32% standard deviation; while 88.34% DSC for HG datasets with 11.77% standard deviation are calculated.

     

Analysis of dynamic magnetic resonance images

Dynamic magnetic resonance (MR) imaging with contrast agents is a very promising technique for studying tissue perfusion in vivo. A temporal series of magnetic resonance images of the same slice are acquired following the injection of a contrast agent into the blood stream. The image intensity depends on the local concentration of the contrast agent, so that tissue perfusion can be studied by the image series. A new method of analyzing such series is described here. Nonparametric linear regression is used for modeling the image intensity along the series on a pixel by pixel basis. After modeling, some relevant quantities describing the time series are obtained and displayed as images. Due to its flexibility, this approach is preferred to parametric modeling when pathology is present since this can induce a wide spread of patterns for the pixel image intensity along time. Results of the application of the method to series of dynamic magnetic resonance images from ischaemic rat brains after the injection of the susceptibility agent Sprodiamide Inj. (Dy-DTPA-BMA) are shown and compared to results from a related known method.     

Area-time trade-offs in arrays with optical pipelined buses

A general model for determining the computational efficiency of a particular class of electro-optical systems is described. The model is an abstraction of parallel systems that use digital electronic processors and optical pipelined buses for communication. Minimum requirements in terms of area (volume for three-dimensional structures) and time necessary in order to solve a problem are obtained. Different applications are investigated, and a matching area-time upper bound is given for the barrel-shift problem, simulated on an array with reconfigurable optical pipelined buses. The types of problems for which these lower bounds seem to be realistic are described.     

Using a Trust Inference Model for Flexible and Controlled Information Sharing During Crises

The fluid, urgent nature of crises requires flexible, responsive information sharing. Recent studies show, however, that in business catastrophes and other kinds of crises conventional access control mechanisms favor security over flexibility. Our work addresses these seemingly contradictory needs for security and flexibility and designs a trust inference model based on fuzzy logic, a model that can be used with pervasive computing technologies using sensors and mobile devices. Drawing upon research on trust, we design a trust inference model using attributes of affiliation, task performance, and urgency; apply the model to a known crisis; discuss implementation issues; and explore issues for further research. This article is dedicated to Alan Jarman, a founding influence in the Journal of Contingencies and Crisis Management who died in Canberra 15 July 2010. Alan's quantitative, engineering background and his long standing commitment to improving crisis decision making prompted him to encourage our applying fuzzy logic to crisis information sharing. We are grateful for Alan's encouragement and advice.     

Accuracy estimate and optimization techniques for SimRank computation

The measure of similarity between objects is a very useful tool in many areas of computer science, including information retrieval. SimRank is a simple and intuitive measure of this kind, based on a graph-theoretic model. SimRank is typically computed iteratively, in the spirit of PageRank. However, existing work on SimRank lacks accuracy estimation of iterative computation and has discouraging time complexity. In this paper, we present a technique to estimate the accuracy of computing SimRank iteratively. This technique provides a way to find out the number of iterations required to achieve a desired accuracy when computing SimRank. We also present optimization techniques that improve the computational complexity of the iterative algorithm from O(n ⁴) in the worst case to min(O(nl), O(n ³/ log₂ n)), with n denoting the number of objects, and l denoting the number object-to-object relationships. We also introduce a threshold sieving heuristic and its accuracy estimation that further improves the efficiency of the method. As a practical illustration of our techniques, we computed SimRank scores on a subset of English Wikipedia corpus, consisting of the complete set of articles and category links.     

Towards Timbre-Invariant Audio Features for Harmony-Based Music

Chroma-based audio features are a well-established tool for analyzing and comparing harmony-based Western music that is based on the equal-tempered scale. By identifying spectral components that differ by a musical octave, chroma features possess a considerable amount of robustness to changes in timbre and instrumentation. In this paper, we describe a novel procedure that further enhances chroma features by significantly boosting the degree of timbre invariance without degrading the features' discriminative power. Our idea is based on the generally accepted observation that the lower mel-frequency cepstral coefficients (MFCCs) are closely related to timbre. Now, instead of keeping the lower coefficients, we discard them and only keep the upper coefficients. Furthermore, using a pitch scale instead of a mel scale allows us to project the remaining coefficients onto the 12 chroma bins. We present a series of experiments to demonstrate that the resulting chroma features outperform various state-of-the art features in the context of music matching and retrieval applications. As a final contribution, we give a detailed analysis of our enhancement procedure revealing the musical meaning of certain pitch-frequency cepstral coefficients.      

Distance browsing in distributed multimedia databases

The state of the art of searching for non-text data (e.g., images) is to use extracted metadata annotations or text, which might be available as a related information. However, supporting real content-based audiovisual search, based on similarity search on features, is significantly more expensive than searching for text. Moreover, such search exhibits linear scalability with respect to the dataset size, so parallel query execution is needed.In this paper, we present a Distributed Incremental Nearest Neighbor algorithm (DINN) for finding closest objects in an incremental fashion over data distributed among computer nodes, each able to perform its local Incremental Nearest Neighbor (local-INN) algorithm. We prove that our algorithm is optimum with respect to both the number of involved nodes and the number of local-INN invocations. An implementation of our DINN algorithm, on a real P2P system called MCAN, was used for conducting an extensive experimental evaluation on a real-life dataset.The proposed algorithm is being used in two running projects: SAPIR and NeP4B.     

Ahead of time static analysis for automatic generation of debugging interfaces to the Linux kernel

The Linux kernel does not export a stable, well-defined kernel interface, complicating the development of kernel-level services, such as device drivers and file systems. While there does exist a set of functions that are exported to external modules, this set of functions frequently changes, and the functions have implicit, ill-documented preconditions. No specific debugging support is provided. We present Diagnosys, an approach to automatically constructing a debugging interface for the Linux kernel. First, a designated kernel maintainer uses Diagnosys to identify constraints on the use of the exported functions. Based on this information, developers of kernel services can then use Diagnosys to generate a debugging interface specialized to their code. When a service including this interface is tested, it records information about potential problems. This information is preserved following a kernel crash or hang. Our experiments show that the generated debugging interface provides useful log information and incurs a low performance penalty.     

Online bin stretching with three bins

Online bin stretching is a semi-online variant of bin packing in which the algorithm has to use the same number of bins as an optimal packing, but is allowed to slightly overpack the bins. The goal is to minimize the amount of overpacking, i.e., the maximum size packed into any bin. We give an algorithm for online bin stretching with a stretching factor of \(11/8 = 1.375\) for three bins. Additionally, we present a lower bound of \(45/33 = 1.\overline{36}\) for online bin stretching on three bins and a lower bound of 19/14 for four and five bins that were discovered using a computer search.