809949
Pubic arch detection in transrectal ultrasound guided prostate cancer therapy
New biopsy techniques, increased life expectancy, and prostate-specific antigen (PSA) screening have contributed to an increase in the reported incidence of prostate cancer. Among several treatment options available to the patients, transperineal prostate brachytherapy has emerged as a medically successful, cost-effective outpatient procedure for treating localized prostate cancer. Transperineal prostate brachytherapy employs transrectal ultrasound (TRUS) as the primary imaging modality to accurately preplan and subsequently execute the placement of radioactive seeds into the prostate. Under TRUS guidance, a needle (preloaded with radioactive seeds) is inserted through a template guide, through the perineum and into a predetermined prostate target. The pubic arch, formed by the central union of pelvic bones, is a potential barrier to the passage of these needles in the prostate. A critical aspect, therefore, in the planning and execution of the brachytherapy procedure is the accurate assessment of pubic arch interference (PAI) in relation to the prostate. Traditionally, the evaluation of PAI has involved computed tomography correlate scanning or crude subjective evaluations. In this paper, the authors describe a new method of assessing PAI by detecting the pubic arch via image processing on the TRUS images. The PAI detection (PAID) algorithm first uses a technique known as sticks to selectively enhance the contrast of linear features in ultrasound images. Next, the enhanced image is thresholded via percentile thresholding. Finally, the authors fit a parabola (a model for the pubic arch) recursively to the thresholded image. Their evaluation result from 15 cases indicates that the algorithm can successfully detect the pubic arch with 90% accuracy. Based on this study, the authors believe that detecting the pubic arch and assessing PAI can be done practically and more accurately in the clinical setting using TRUS rather than the current available methods.
8647579
MediaStation 5000: integrating video and audio
MediaStation 5000 is a highly integrated desktop multimedia system implemented on a single PC plug-in board. It performs multistandard compression, high-speed image processing, and fast 2D and 3D graphics functions. The Texas instruments Multimedia Video Processor (MVP), a single-chip multiprocessing device with a highly parallel internal architecture, provides the system's processing power and programmability.<<ETX>>
40331728
Efficient 2-D Convolution Algorithm with the Single-Data Multiple Kernel Approach
Abstract A fast implementation of convolution operation is described. The implementation takes advantage of various properties of commonly used kernels. First, the kernel elements are analyzed and rearranged, grouping the kernel elements of the same absolute value together and arranging trivial multiplication cases separately. Then the sequence of computing convolution sums is modified so that all the kernel elements could be multiplied by the same data element at each step. This new algorithm significantly reduces the number of multiplication operations for most widely used kernels. Our experiment shows that the performance improvement of two to seven over the direct implementation is achievable for most kernels. The required overhead (extra memory and preprocessing) is proportional to the kernel size and is negligible.
12493055
A methodology for evaluation of boundary detection algorithms on medical images
Image segmentation is the partition of an image into a set of nonoverlapping regions whose union is the entire image. The image is decomposed into meaningful parts which are uniform with respect to certain characteristics, such as gray level or texture. In this paper, we propose a methodology for evaluating medical image segmentation algorithms wherein the only information available is boundaries outlined by multiple expert observers. In this case, the results of the segmentation algorithm can be evaluated against the multiple observers' outlines. We have derived statistics to enable us to find whether the computer-generated boundaries agree with the observers' hand-outlined boundaries as much as the different observers agree with each other. We illustrate the use of this methodology by evaluating image segmentation algorithms on two different applications in ultrasound imaging. In the first application, we attempt to find the epicardial and endocardial boundaries from cardiac ultrasound images, and in the second application, our goal is to find the fetal skull and abdomen boundaries from prenatal ultrasound images.
9437835
Computing Requirements of Modern Medical Diagnostic Ultrasound Machines
Abstract Ultrasound is one of the leading medical imaging modalities because it is safe, noninvasive, portable, easy to use, relatively inexpensive and displays images in real-time. Due to its real-time nature, an ultrasound machine must be able to process its incoming data quickly. High computational and throughput requirements in modern ultrasound machines have restricted their internal design to algorithm-specific hardware with limited programmability. Adding new ultrasound imaging applications or improving a machine's internal algorithms can require costly hardware redesigns and replacements of boards or of the entire machine. In an effort to address these problems, we have reviewed each of the essential functions in modern ultrasound machines and analyzed their computational requirements in programmable systems. These functions include dynamic downconversion, tissue signal processing, color flow processing, scan conversion, and tissue/flow decision. Our estimate of the total computing requirement to current ultrasound machines is 54.71 billion operations per second (BOPS) when transcendental functions are implemented in software and 31.26 BOPS when transcendental functions are implemented in lookup tables taking 160.26 Mbytes of memory. To investigate the feasibility of programmable generalized ultrasound systems, we have designed a flexible and parallel programmable ultrasound processing subsystem, called the Programmable Ultrasound Image Processor (PUIP). As the need for programmable ultrasound machines increases in the future due to various advantages (e.g., lower system cost, faster clinical use and lower research/development expenses), it will be crucial to develop not only a high-performance, scalable, reconfigurable parallel computer architecture meeting the computing requirement, but also efficient ultrasound algorithms that can be optimally mapped into the parallel architecture.
260546
Realistic Sensing Area Modeling
Despite the well-known fact that sensing patterns in reality are highly irregular, researchers continue to develop protocols with simplifying assumptions about the sensing. For example, a circular 0/1 sensing model is widely used in most existing simulators and analysis. While this model provides high-level guidelines, it could cause wrong estimation of system performance in the real world. In this project, we design and implement a practical Sensing Area Modeling technique, called SAM. By injecting events through regular and hierarchical training, SAM estimates the sensing areas of individual sensor nodes accurately. Especially, this work is the first to investigate the impact of irregular sensing area on application performance, such as coverage scheduling. We evaluate SAM using outdoor experiments with XSM motes, indoor experiment with 40 MicaZ motes as well as an extensive 1000-node simulation. Our evaluation results reveal serious problems caused by circular sensing model, while demonstrating significant performance improvements in major applications when SAM is used.
6315809
On the performance of group key agreement protocols
Group key agreement is a fundamental building block for secure peer group communication systems. Several group key management techniques were proposed in the last decade, all assuming the existence of an underlying group communication infrastructure to provide reliable and ordered message delivery as well as group membership information. Despite analysis, implementation, and deployment of some of these techniques, the actual costs associated with group key management have been poorly understood so far. This resulted in an undesirable tendency: on the one hand, adopting suboptimal security for reliable group communication, while, on the other hand, constructing excessively costly group key management protocols.This paper presents a thorough performance evaluation of five notable distributed key management techniques (for collaborative peer groups) integrated with a reliable group communication system. An in-depth comparison and analysis of the five techniques is presented based on experimental results obtained in actual local- and wide-area networks. The extensive performance measurement experiments conducted for all methods offer insights into their scalability and practicality. Furthermore, our analysis of the experimental results highlights several observations that are not obvious from the theoretical analysis.
36946020
Face Representation Method Using Pixel-to-Vertex Map (PVM) for 3D Model Based Face Recognition
3D model based approach for face recognition has been spotlighted as a robust solution under variant conditions of pose and illumination. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time. In this paper, we propose a novel 3D face representation algorithm to reduce the number of vertices and optimize its computation time. Finally, we evaluate the performance of proposed algorithm with the Korean face database collected using a stereo-camera based 3D face capturing device.
6477815
An Affective User Interface Based on Facial Expression Recognition and Eye-Gaze Tracking
This paper describes a pipeline by which facial expression and eye-gaze of the user are tracked, and then 3D facial animation is synthesized in the remote place based upon timing information of the facial and eye movement information. The system first detects a facial area within the given image and then classifies its facial expression into 7 emotional weightings. Such weighting information, transmitted to the PDA via a mobile network, is used for non-photorealistic facial expression animation. It turns out that facial expression animation using emotional curves is more effective in expressing the timing of an expression comparing to the linear interpolation method. The emotional avatar embedded on a mobile platform has some potential in conveying emotion between peoples via Internet.
14743541
SCAI TREC-8 Experiments
This working note reports our experiences with TREC-8 on four tracks: Ad Hoc, Filtering, Web, and QA. The Ad Hoc retrieval engine, SCAIR, has been used for the Web and QA experiments, and the ltering experiments were based on it's own engine. As a second entry to TREC, we focused this year on exploring possibilities of applying machine learning techniques to TREC tasks. The Ad Hoc track employed a cluster-based retrieval method where the scoring function used cluster information extracted from a collection of precompiled documents. Filtering was based on naive Bayes learning supported by an EM algorithm. In the Web track, we compared the performance of using link information to that of not using the information. In the QA track, some passage extraction techniques have been tested using the baseline SCAIR retrieval engine.