Medical imaging provides physicians with the ability to generate 3D images of the human body in order to detect and diagnose a wide variety of ailments. Making medical imaging portable and more accessible provides a u...
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ISBN:
(纸本)9781450301787
Medical imaging provides physicians with the ability to generate 3D images of the human body in order to detect and diagnose a wide variety of ailments. Making medical imaging portable and more accessible provides a unique set of challenges. In order to increase portability, the power consumed in image acquisition - currently the most power-consuming activity in an imaging device - must be dramatically reduced. This can only be done, however, by using complex image reconstruction algorithms to correct artifacts introduced by low-power acquisition, resulting in image processing becoming the dominant power-consuming task. Current solutions use combinations of digital signal processors, general-purpose processors and, more recently, general-purpose graphics processing units for medical image processing. These solutions fall short for various reasons including high power consumption and an inability to execute the next generation of image reconstruction algorithms. This paper presents the MEDICS architecture a domain-specific multicore architecture designed specifically for medical imaging applications, but with sufficient generality to make it programmable. The goal is to achieve 100 GFLOPs of performance while consuming orders of magnitude less power than the existing solutions. MEDICS has a throughput of 128 GFLOPs while consuming as little as 1.6W of power on advanced CT reconstruction applications. This represents up to a 20x increase in computation efficiency over current designs.
Beam-based adaptive processing is an economical way to achieve good interference rejection performance from an adaptive receiving array, at much less computational cost than full element-based methods. However, to exp...
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Beam-based adaptive processing is an economical way to achieve good interference rejection performance from an adaptive receiving array, at much less computational cost than full element-based methods. However, to exploit this potential for planar arrays it is necessary to identify, in real time, which beams must be retained for adaptive cancellation. This paper analyzes the beam-selection problem and presents a computationally efficient algorithm that performs real-time beam selection.
An iterative solution is given for solving deblurring problems having nonnegativity constraints through the use of methods motivated by tomographic imaging. After briefly reviewing three versions of tomographic-imagin...
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An iterative solution is given for solving deblurring problems having nonnegativity constraints through the use of methods motivated by tomographic imaging. After briefly reviewing three versions of tomographic-imaging problems, the paper indicates how methods that have proven to be powerful for the third version, weighted-integral tomography, can be applied to the more general deblurring problem when nonnegativity constraints are present.
We use time-frequency distributions to define local stationarity of a random process. We argue that local stationarity is achieved when the Wigner spectrum is approximately factorable. We show that when that is the ca...
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ISBN:
(纸本)0819463922
We use time-frequency distributions to define local stationarity of a random process. We argue that local stationarity is achieved when the Wigner spectrum is approximately factorable. We show that when that is the case the autocorrelation function is the one considered by Silverman in 1957. Other time-frequency represenations are also considered.
advancedalgorithms for synthetic aperture radar (SAR) imaging have in the past required computing capabilities only available from high performance special purpose hardware. Such architectures have tended to have sho...
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ISBN:
(纸本)0819415340
advancedalgorithms for synthetic aperture radar (SAR) imaging have in the past required computing capabilities only available from high performance special purpose hardware. Such architectures have tended to have short life cycles with respect to development expense. Current generation Massively Parallel Processors (MPP) are offering high performance capabilities necessary for such applications with both a scalable architecture and a longer projected life cycle. In this paper we explore issues associated with implementation of a SAR imaging algorithm on a mesh configured MPP architecture.
We develop an algorithm for adaptively estimating the noise subspace of a data matrix, as is required in signalprocessing applications employing the 'signal subspace' approach. The noise subspace is estimated...
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The performances of high-resolution array processing methods are known to degrade in random inhomogeneous media because the amplitude and phase of each wavefront tend to fluctuate and to loose their coherence between ...
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The performances of high-resolution array processing methods are known to degrade in random inhomogeneous media because the amplitude and phase of each wavefront tend to fluctuate and to loose their coherence between array sensors. As a result, in the presence of such a multiplicative noise, the conventional coherent wavefront model becomes inapplicable. Such a type of degradation may be especially strong for large aperture arrays. Below, we develop new high-resolution covariance matching (CM) techniques with an improved robustness against multiplicative noise and related coherence losses. Using a few unrestrictive physics-based assumptions on the environment, we show that reliable algorithms can be developed which take into account possible coherence losses. Computer simulation results and real sonar data processing results are presented. These results demonstrate drastic improvements achieved by our approach as compared with conventional high-resolution array processing techniques.
In this paper, an adaptive algorithm for direction-finding of correlated sources is presented. The algorithm is low in computational complexity and it does not require determination of the effective rank of the array ...
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In this paper, an adaptive algorithm for direction-finding of correlated sources is presented. The algorithm is low in computational complexity and it does not require determination of the effective rank of the array correlation matrix. The algorithm employs a gradient technique to determine the minimum eigenvector of the correlation matrix and an orthogonalization technique to determine the second minimum eigenvector. The two noise eigenvectors are then used to compute the spatial spectra. The angle of arrivals can then be found by superimposing the two spectra. To verify further the true arrivals, additional spatial spectral can be computed using a combination of the two noise eigenvectors. Numerical results show that the proposed algorithms are effective in resolving correlated sources.
Working with the Naval Research Laboratory, Celestech has implemented advanced non-linear hyperspectral image (HSI) processingalgorithms optimized for Graphics processing Units (GPU). These algorithms have demonstrat...
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ISBN:
(纸本)9780819481597
Working with the Naval Research Laboratory, Celestech has implemented advanced non-linear hyperspectral image (HSI) processingalgorithms optimized for Graphics processing Units (GPU). These algorithms have demonstrated performance improvements of nearly 2 orders of magnitude over optimal CPU-based implementations. The paper briefly covers the architecture of the NIVIDIA GPU to provide a basis for discussing GPU optimization challenges and strategies. The paper then covers optimization approaches employed to extract performance from the GPU implementation of Dr. Bachmann's algorithms including memory utilization and process thread optimization considerations. The paper goes on to discuss strategies for deploying GPU-enabled servers into enterprise service oriented architectures. Also discussed are Celestech's on-going work in the area of middleware frameworks to provide an optimized multi-GPU utilization and scheduling approach that supports both multiple GPUs in a single computer as well as across multiple computers. This paper is a complementary work to the paper submitted by Dr. Charles Bachmann entitled "A Scalable Approach to Modeling Nonlinear Structure in Hyperspectral Imagery and Other High-Dimensional Data Using Manifold Coordinate Representations". Dr. Bachmann's paper covers the algorithmic and theoretical basis for the HSI processing approach.
This paper presents the application of the Linear Sequential Array (LSA) retiming approach, developed for conventional digit-recurrence algorithms, to on-line multiplication. The result is a modular and fast pipelined...
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This paper presents the application of the Linear Sequential Array (LSA) retiming approach, developed for conventional digit-recurrence algorithms, to on-line multiplication. The result is a modular and fast pipelined structure which due to a small constant fan-out and cycle time independent of precision is suitable for FPGA implementation. First we present the basics of on-line multiplication, and determine data dependencies according to the LSA design methodology. Based on these dependencies we redesign the traditional on-line multiplier to obtain the LSA structure. Since in DSP applications one of the multiplier operands is fixed for a long sequence of operations, we briefly present a parallel-serial multiplication unit that receives one of the operands in parallel and the other operand in Most-Significant-Digit-First format. Performance and area results are provided for the LSA on-line multiplier design and then compared with the conventional on-line design, using xilinx FPGAs as the target technology.
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