Combination Of Spatial Filtering Research Articles

Virtual MEG sensors based on beamformer and independent component analysis can reconstruct epileptic activity as measured on simultaneous intracerebral recordings

The prevailing gold standard for presurgical determination of epileptogenic brain networks is intracerebral EEG, a potent yet invasive approach. Magnetoencephalography (MEG) is a state-of-the art non-invasive method for investigating epileptiform discharges. However, it is not clear at what level the precision offered by MEG can reach that of SEEG. Here, we present a strategy for non-invasively retrieving the constituents of the interictal network, with high spatial and temporal precision. Our method is based on MEG and a combination of spatial filtering and independent component analysis (ICA). We validated this approach in twelve patients with drug-resistant focal epilepsy, thanks to the unprecedented ground truth provided by simultaneous recordings of MEG and SEEG. A minimum variance adaptive beamformer estimated the source time series and ICA was used to further decompose these time series into network constituents (MEG-ICs), each having a time series (virtual electrode) and a topography (spatial distribution of amplitudes in the brain). We show that MEG has a considerable sensitivity of 0.80 and 0.84 and a specificity of 0.93 and 0.91 for reconstructing deep and superficial sources, respectively, when compared to the ground truth (SEEG). For each epileptic MEG-IC (n = 131), we found at least one significantly correlating SEEG contact close to zero lag after correcting for multiple comparisons. All the patients except one had at least one epileptic component that was highly correlated (Spearman rho>0.3) with that of SEEG traces. MEG-ICs correlated well with SEEG traces. The strength of correlation coefficients did not depend on the depth of the SEEG contacts or the clinical outcome of the patient. A significant proportion of the MEG-ICs (n = 83/131) were localized in proximity with their maximally correlating SEEG, within a mean distance of 20±12.18mm. Our research is the first to validate the MEG-retrieved beamformer IC sources against SEEG-derived ground truth in a simultaneous MEG-SEEG framework. Observations from the present study suggest that non-invasive MEG source components may potentially provide additional information, comparable to SEEG in a number of instances.

Combining Spatial Filtering and Sparse Filtering for Coaxial-Moving Sound Source Separation, Enhancement and Fault Diagnosis

The wayside acoustic detector system is a potential technique in ensuring the safety of traveling vehicles. However, multisource aliasing and Doppler distortion in acquired acoustic signals decrease the accuracy of machine diagnosis. The conventional multisource separation schemes fail to solve the coaxial-moving sound source (CMSS) problem by constructing time–frequency filters and designing one-dimensional time-varying spatial filters. To address this issue, this paper combines spatial filtering with sparse filtering to solve this problem. Spatial filtering could suppress but not eliminate undesired sources. Sparse filtering has no capability of coping with non-stationary signals with Doppler distortion. The combination of spatial filtering and sparse filtering could make up their shortcomings and effectively solve the CMSS problem. The proposed scheme has two main advantages of eliminating residual interferences completely and suppressing background noise effectively. The simulation and experimental cases verify the effectiveness of the proposed method. The results indicate the potential of the proposed method to improve the performance of wayside acoustic detector systems.

Combination of Spatial Filtering and Adaptive Wavelet Thresholding for Image Denoising

Combination of Spatial Filtering and Adaptive Wavelet Thresholding for Image Denoising

Five Micron High Resolution MALDI Mass Spectrometry Imaging with Simple, Interchangeable, Multi-Resolution Optical System.

High-spatial resolution mass spectrometry imaging (MSI) is crucial for the mapping of chemical distributions at the cellular and subcellular level. In this work, we improved our previous laser optical system for matrix-assisted laser desorption ionization (MALDI)-MSI, from ~9 μm practical laser spot size to a practical laser spot size of ~4 μm, thereby allowing for 5 μm resolution imaging without oversampling. This is accomplished through a combination of spatial filtering, beam expansion, and reduction of the final focal length. Most importantly, the new laser optics system allows for simple modification of the spot size solely through the interchanging of the beam expander component. Using 10×, 5×, and no beam expander, we could routinely change between ~4, ~7, and ~45 μm laser spot size, in less than 5 min. We applied this multi-resolution MALDI-MSI system to a single maize root tissue section with three different spatial resolutions of 5, 10, and 50 μm and compared the differences in imaging quality and signal sensitivity. We also demonstrated the difference in depth of focus between the optical systems with 10× and 5× beam expanders. Graphical Abstract ᅟ.

FIRST, a fibered aperture masking instrument

In this paper we present the first on-sky results with the fibered aperture masking instrument FIRST. Its principle relies on the combination of spatial filtering and aperture masking using single-mode fibers, a novel technique that is aimed at high dynamic range imaging with high angular resolution. The prototype has been tested with the Shane 3-m telescope at Lick Observatory. The entrance pupil is divided into subpupils feeding single-mode fibers. The flux injection into the fibers is optimized by a segmented mirror. The beams are spectrally dispersed and recombined in a non-redundant exit configuration in order to retrieve all contrasts and phases independently. The instrument works at visible wavelengths between 600 nm and 760 nm and currently uses nine of the 30 43 cm subapertures constituting the full pupil. First fringes were obtained on Vega and Deneb. Stable closure phases were measured with standard deviations on the order of 1 degree. Closure phase precision can be further improved by addressing some of the remaining sources of systematic errors. While the number of fibers used in the experiment was too small to reliably estimate visibility amplitudes, we have measured closure amplitudes with a precision of 10 % in the best case. These first promising results obtained under real observing conditions validate the concept of the fibered aperture masking instrument and open the way for a new type of ground-based instrument working in the visible. The next steps of the development will be to improve the stability and the sensitivity of the instrument in order to achieve more accurate closure phase and visibility measurements, and to increase the number of sub-pupils to reach full pupil coverage.

Enhancement of Degraded Historical Kannada Documents

documents play a vital role in understanding our past and hence need to be preserved. Over the period, these documents tend to possess many variations like stains, strain, ink seepage, dust etc. Image enhancement techniques can be utilized to improve the quality of these images by removing noise and increasing contrast range. The proposed method mainly deals with enhancing the historical document image of palm scripts using gray scale morphological operations with the combination of spatial filters. Morphological opening operation is applied to compensate for non uniform background intensity and suppress bright details smaller than the structural element, while closing suppresses the dark details. The proposed method works well for the images with dark background and low contrast and enhances the image with clear white background.

Binocular robot vision emulating disparity computation in the primary visual cortex

We designed a VLSI binocular vision system that emulates the disparity computation in the primary visual cortex (V1). The system consists of two silicon retinas, orientation chips, and field programmable gate array (FPGA), mimicking a hierarchical architecture of visual information processing in the disparity energy model. The silicon retinas emulate a Laplacian-Gaussian-like receptive field of the vertebrate retina. The orientation chips generate an orientation-selective receptive field by aggregating multiple pixels of the silicon retina, mimicking the Hubel-Wiesel-type feed-forward model in order to emulate a Gabor-like receptive field of simple cells. The FPGA receives outputs from the orientation chips corresponding to the left and right eyes and calculates the responses of the complex cells based on the disparity energy model. The system can provide the responses of complex cells tuned to five different disparities and a disparity map obtained by comparing these energy outputs. Owing to the combination of spatial filtering by analog parallel circuits and pixel-wise computation by hard-wired digital circuits, the present system can execute the disparity computation in real time using compact hardware.

Incorporation of acoustic normal mode data into tomographic inversions in the Greenland Sea

Acoustic normal mode group velocity data are extracted from tomographic receptions in the Greenland Sea using a combination of spatial filtering with data from a six‐element hydrophone array and variable time windowing. The mode group velocity data, together with ray travel time data, are used in inversions to obtain the range average sound speed profile. The modal data significantly improve near‐surface resolution, which is where the largest oceanographic signals occur. Inverse results using only acoustic data are consistent with point measurements, a Seasoar section, and sparse conductivity‐temperature‐depth data.

Nonlinear operators for improving texture segmentation based on features extracted by spatial filtering

An unsupervised texture segmentation system using texture features obtained from a combination of spatial filters and nonlinear operators is described. Local texture features are evaluated in parallel by a succession of four basic operations: (1) a convolution for local structure detection (local linear transform); (2) a first nonlinearity of the form f(x)= mod x mod /sup alpha /; (3) an iterative smoothing operator; and (4) a second nonlinearity g(x). The Karhunen-Loeve transform is used to reduce the dimensionality of the resulting feature vector, and segmentation is achieved by thresholding or clustering in feature space. The combination of nonlinearities f(x)= mod x mod /sup alpha / (in particular, alpha =2) and g(x)=log x maximizes texture discrimination, and results in a description with variances approximately constant for all feature components and texture regions. This latter property improves the performance of both feature reduction and clustering algorithms significantly. >

Degenerate four-wave mixing as a spectrochemical analysis technique

The nonlinear spectroscopic technique of degenerate four-wave mixing (DFWM) is studied theoretically and experimentally for use as a spectrochemical analysis tool. Specifically, DFWM was evaluated for use in flame elemental analysis. The theoretical evaluation indicates that detection is fundamentally limited by Rayleigh scattering from flame gases. For the case of sodium this detection limit is estimated to be 0.01 pptr (part per trillion) or 10 fg/mL. A pulsed Nd:YAG pumped dye laser was used for the experimental study where aqueous solutions of sodium were aspirated into an air-C/sub 2/H/sub 2/ flame. A combination of spatial filtering, polarization selection, and time resolution is used to discriminate against background signals. A measured detection limit of 4 ppb sodium is obtained. Improved detection limits are expected for a continuous wave laser system.