作者：
Rao, Raghu Ambekar RamachandraToussaint Jr., Kimani C.
Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL 61801 United States
Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign Urbana IL 61801 United States
Departments of Electrical and Computer Engineering Bioengineering Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign Urbana IL 61801 United States
We discuss the application of harmonic analysis in second-harmonic generation microscopy in developing useful quantitative metrics for assessing tissue morphology. A comparison between the information content in forwa...
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Artificial Immune Systems (AISs) are composed of techniques inspired by immunology. The clonal selection principle ensures the organism adaptation to fight invading antigens by an immune response activated by the bind...
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作者：
Ambekar Ramachandra Rao, RaghuMehta, Monal R.Leithem, ScottToussaint Jr., Kimani C.
Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign IL 61820 United States
Department of Mechanical Science and Engineering University of Illinois Urbana-Champaign IL 61820 United States
Departments of Electrical and Computer Engineering and Bioengineering University of Illinois Urbana-Champaign IL 61820 United States
Fourier transform-second-harmonic generation imaging is presented to quantitatively describe the collagen fiber organization in biological tissues. Further, we use this technique to compare the information content in ...
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The paper employed some independently developed sensors based on the Octopus X platform to build a Zigbee-based Sensor Networks. Also, we implemented a Location-aware living environment by deploying the developed Zige...
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K562 mammalian cells are sorted using a highly integrated microfabricated fluorescence-activated cell sorter (μFACS). The sample cells are purified with an enrichment factor of 230 at a high throughput (>1,000 cel...
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In recent years,much attention has been given to the increase in the Earth-Sun distance,with the modern rate reported as 5-15 m/cy on the basis of astronomical ***,traditional methods cannot measure the ancient leavin...
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In recent years,much attention has been given to the increase in the Earth-Sun distance,with the modern rate reported as 5-15 m/cy on the basis of astronomical ***,traditional methods cannot measure the ancient leaving rates,so a myriad of research attempting to provide explanations were met with unmatched *** this paper we consider that the growth patterns on fossils could reflect the ancient Earth-Sun *** mechanical analysis of both the Earth-Sun and Earth-Moon systems,these patterns confirmed an increase in the Earth-Sun *** a large number of well-preserved specimens and new technology available,both the modern and ancient leaving rates could be measured with high precision,and it was found that the Earth has been leaving the Sun over the past 0.53 billion *** Earth's semi-major axis was 146 million kilometers at the beginning of the Phanerozoic Eon,equating to 97.6% of its current *** modern leaving rates are 5-14 m/cy,whereas the ancient rates were much *** results indicate a special expansion with an average expansion coefficient of 0.57H0 and deceleration in the form of Hubble *** the basis of experimental results,the Earth's semi-major axis could be represented by a simple formula that matches fossil measurements.
The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model...
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The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence- termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carr
The use of MEMS to study the effect of mechanical compression on neurogenesis has been demonstrated. Polydimethylsiloxane- (PDMS)-based stretchable platforms were used on neurosphere assay to investigate the role of m...
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Magnetic resonance elastography (MRE) is an emerging technique for noninvasive imaging of tissue elasticity. Proprietary algorithms are used to reconstruct tissue elasticity from the images of wave propagation within ...
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ISBN:
(纸本)9783642156984
Magnetic resonance elastography (MRE) is an emerging technique for noninvasive imaging of tissue elasticity. Proprietary algorithms are used to reconstruct tissue elasticity from the images of wave propagation within soft tissue. Elasticity reconstruction suffers from interfering noise and outliers. The interference causes biased elasticity and undesired artifacts in the reconstructed elasticity map. Anisotropic geometric diffusion is able to suppress image noise while enhance inherent features. Therefore we integrate anisotropic diffusion with level set methods for numerical enhancement of MRE wave images. Performance evaluation of the proposed level set diffusion (LSD) approach was conducted on both synthetic and real MRE datasets. Experimental results confirm the effectiveness of LSD for MRE image enhancement and direct inversion.
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