Search results for "Signal-to-noise ratio"
showing 10 items of 96 documents
TAF-ChIP: an ultra-low input approach for genome-wide chromatin immunoprecipitation assay
2019
The authors present a novel method for obtaining chromatin profiles from low cell numbers without prior nuclei isolation. The method is successfully implemented in generating epigenetic profile from 100 cells with high signal-to-noise ratio.
Interval Length Analysis in Multi Layer Model
2009
In this paper we present an hypothesis test of randomness based on the probability density function of the symmetrized Kulback-Leibler distance estimated, via a Monte Carlo simulation, by the distributions of the interval lengths detected using the Multi-Layer Model (MLM). The $MLM$ is based on the generation of several sub-samples of an input signal; in particular a set of optimal cut-set thresholds are applied to the data to detect signal properties. In this sense MLM is a general pattern detection method and it can be considered a preprocessing tool for pattern discovery. At the present the test has been evaluated on simulated signals which respect a particular tiled microarray approach …
Quantitative comparison of new image processing methods for volumetric analysis of left ventricular contrast echocardiograms
2003
An effort has been made to develop image processing methods which allow a definite and precise tracking of the borderline of the ventricle in two-dimensional echocardiograms. Experience is reported with two new methods, which are based on the gray-level rise (GL) and the signal-to-noise ratio (SNR) in combined heart-phase-triggered image series. A quantitative comparison of these time-series methods is presented with respect to the interpretation of a single native image (noncontrast image), a single contrast-material image, the corresponding subtraction image, and the corresponding color superposition image. The comparison is based on the calculation of the ejection fraction using the abov…
Learning with the kernel signal to noise ratio
2012
This paper presents the application of the kernel signal to noise ratio (KSNR) in the context of feature extraction to general machine learning and signal processing domains. The proposed approach maximizes the signal variance while minimizes the estimated noise variance in a reproducing kernel Hilbert space (RKHS). The KSNR can be used in any kernel method to deal with correlated (possibly non-Gaussian) noise. We illustrate the method in nonlinear regression examples, dependence estimation and causal inference, nonlinear channel equalization, and nonlinear feature extraction from high-dimensional satellite images. Results show that the proposed KSNR yields more fitted solutions and extract…
Explicit signal to noise ratio in reproducing kernel Hilbert spaces
2011
This paper introduces a nonlinear feature extraction method based on kernels for remote sensing data analysis. The proposed approach is based on the minimum noise fraction (MNF) transform, which maximizes the signal variance while also minimizing the estimated noise variance. We here propose an alternative kernel MNF (KMNF) in which the noise is explicitly estimated in the reproducing kernel Hilbert space. This enables KMNF dealing with non-linear relations between the noise and the signal features jointly. Results show that the proposed KMNF provides the most noise-free features when confronted with PCA, MNF, KPCA, and the previous version of KMNF. Extracted features with the explicit KMNF…
A new tuning parameter selector in lasso regression
2019
Penalized regression models are popularly used in high-dimensional data analysis to carry out variable selction and model fitting simultaneously. Whereas success has been widely reported in literature, their performance largely depend on the tuning parameter that balances the trade-off between model fitting and sparsity. In this work we introduce a new tuning parameter selction criterion based on the maximization of the signal-to-noise ratio. To prove its effectiveness we applied it to a real data on prostate cancer disease.
Lossless and near-lossless image compression based on multiresolution analysis
2013
There are applications in data compression, where quality control is of utmost importance. Certain features in the decoded signal must be exactly, or very accurately recovered, yet one would like to be as economical as possible with respect to storage and speed of computation. In this paper, we present a multi-scale data-compression algorithm within Harten's interpolatory framework for multiresolution that gives a specific estimate of the precise error between the original and the decoded signal, when measured in the L"~ and in the L"p (p=1,2) discrete norms. The proposed algorithm does not rely on a tensor-product strategy to compress two-dimensional signals, and it provides a priori bound…
Comparison of Diffusion MRI Acquisition Protocols for the In Vivo Characterization of the Mouse Spinal Cord: Variability Analysis and Application to …
2016
Diffusion-weighted Magnetic Resonance Imaging (dMRI) has relevant applications in the microstructural characterization of the spinal cord, especially in neurodegenerative diseases. Animal models have a pivotal role in the study of such diseases; however, in vivo spinal dMRI of small animals entails additional challenges that require a systematical investigation of acquisition parameters. The purpose of this study is to compare three acquisition protocols and identify the scanning parameters allowing a robust estimation of the main diffusion quantities and a good sensitivity to neurodegeneration in the mouse spinal cord. For all the protocols, the signal-to-noise and contrast-to noise ratios…
Imaging of Orthotopic Glioblastoma Xenografts in Mice Using a Clinical CT Scanner: Comparison with Micro-CT and Histology
2016
Purpose There is an increasing need for small animal in vivo imaging in murine orthotopic glioma models. Because dedicated small animal scanners are not available ubiquitously, the applicability of a clinical CT scanner for visualization and measurement of intracerebrally growing glioma xenografts in living mice was validated. Materials and Methods 2.5x106 U87MG cells were orthotopically implanted in NOD/SCID/ᵞc-/- mice (n = 9). Mice underwent contrast-enhanced (300 μl Iomeprol i.v.) imaging using a micro-CT (80 kV, 75 μAs, 360° rotation, 1,000 projections, scan time 33 s, resolution 40 x 40 x 53 μm) and a clinical CT scanner (4-row multislice detector; 120 kV, 150 mAs, slice thickness 0.5 …
Improved contrast for myeloma focal lesions with T2-weighted Dixon images compared to T1-weighted images
2019
International audience; Purpose: The purpose of this study was twofold. First, to compare the contrast between spinal multiple myeloma (MM) focal lesions and surrounding bone marrow obtained on T2-weighted Dixon fat-only MR images to that obtained on T1-weighted spin-echo images. Second, to search for correlation between bone marrow fat fraction assessed by T2-weighted Dixon sequence and International Myeloma Working Group myeloma defining events.Materials and methods: A total of 39 patients with 112 focal MM lesions were included. There were 25 men and 14 women with a mean age of 68.8±9.8 [SD] years (range: 49-88 years). Contrast between focal MM lesions and surrounding bone marrow was cal…