95 results about "Spectral variation" patented technology

A method and apparatus are provided for noninvasive sampling. More particularly, the method and apparatus relate to control of motion of an optical sample probe interface relative to a tissue sample site. A dynamic probe interface, is used to collect spectra of a targeted sample, control positioning of the sample probe relative to the tissue sample in terms of at least one of x-, y-, and z-axes, and / or control of sample tissue displacement to minimize spectral variations resulting from the sampling process and increase analyte property estimation precision and accuracy.

A method of endpoint detection during plasma processing of a semiconductor wafer comprises processing a semiconductor wafer using a plasma, detecting radiation emission from the plasma during the semiconductor processing, and tracking data points representing changes in spectra of the radiation as a function of time during the semiconductor processing. At any point prior to or during processing a plurality of profiles are provided, each profile representing a different processing condition affecting detection of the desired plasma processing endpoint of the semiconductor wafer. After selecting a desired profile, a first set of parameters are input, representing simplified values for determining when changes in spectra of the radiation indicate that plasma processing of the semiconductor wafer reaches a desired endpoint. The selected profile converts the input first set of parameters into a larger, second set of parameters, and then applies the second set of parameters to an algorithm that converts data points from the spectra of the radiation as a function of time into an endpoint curve. The method then uses the algorithm to track changes in spectra of the radiation as a function of time and determine when plasma processing of the semiconductor wafer reaches a desired endpoint.

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

The present invention provides a method and an apparatus for the in vivo, non-invasive, early detection of alterations and mapping of the grade of these alterations, caused in the biochemical and / or in the functional characteristics of epithelial tissues during the development of tissue atypias, dysplasias, neoplasias and cancers. The method is based, at least in part, on the simultaneous measurement of the spatial, temporal and spectral alterations in the characteristics of the light that is re-emitted from the tissue under examination, as a result of a combined tissue excitation with light and special chemical agents. The topical or systematic administration of these agents result in an evanescent contrast enhancement between normal and abnormal areas of tissue. The apparatus enables the capturing of temporally successive imaging in one or more spectral bands simultaneously. Based on the measured data, the characteristic curves that express the agent-tissue interaction kinetics, as well as numerical parameters derived from these data, are determined in any spatial point of the examined area. Mapping and characterization of the lesion, are based on these parameters.

A method of and a system for spectral correction in multi-energy computed tomography are provided to correct reconstructed images, including high-energy CT images and Z (effective atomic number) images, for spectral variations, which include time variations on a scanner due to HVPS drift and scanner to scanner variations due to the beamline component differences. The method uses a copper filter mounted on the detector array for tracking the spectral changes. The method comprises: generating copper ratios; computing working air tables; calculating scales and offsets; and correcting high-energy CT images and Z images using calculated scales and offsets. The method further includes an off-line calibration procedure to generate necessary parameters for the online correction.

An optical method for measuring the temperature of a substrate material with a temperature dependent band edge. In this method both the position and the width of the knee of the band edge spectrum of the substrate are used to determine temperature. The width of the knee is used to correct for the spurious shifts in the position of the knee caused by: (i) thin film interference in a deposited layer on the substrate; (ii) anisotropic scattering at the back of the substrate; (iii) the spectral variation in the absorptance of deposited layers that absorb in the vicinity of the band edge of the substrate; and (iv) the spectral dependence in the optical response of the wavelength selective detection system used to obtain the band edge spectrum of the substrate. The adjusted position of the knee is used to calculate the substrate temperature from a predetermined calibration curve. This algorithm is suitable for real-time applications as the information needed to correct the knee position is obtained from the spectrum itself. Using a model for the temperature dependent shape of the absorption edge in GaAs and InP, the effect of substrate thickness and the optical geometry of the method used to determine the band edge spectrum, are incorporated into the calibration curve.

The invention relates to noninvasive sampling. In one embodiment, the invention relates to a sample probe interface method and apparatus for targeting a tissue depth and / or pathlength that is used in conjunction with a noninvasive analyzer to control spectral variation. In a second embodiment, a signal from a sample or target probe of a tissue feature or volume is used in positioning a portion of a measuring system relative to the sample. The system is optionally used in conjunction with a targeting system used to control the sampling location of the measuring system.

The present invention relates to methods and compositions for the direct detection of analytes using observable spectral changes in biopolymeric systems. In particular, the present invention allows for the direct colorimetric detection of analytes using color changes that occur in glycopolythiophene polymer systems in response to selective binding of analytes.

The invention relates to noninvasive sampling. In one embodiment, the invention relates to a sample probe interface method and apparatus for targeting a tissue depth and / or pathlength that is used in conjunction with a noninvasive analyzer to control spectral variation. In a second embodiment, a signal from a sample or target probe of a tissue feature or volume is used in positioning a portion of a measuring system relative to the sample. The system is optionally used in conjunction with a targeting system used to control the sampling location of the measuring system.

A digital image monitoring system with functions of motion detection and auto iris which aims at the requirement of video-recording monitoring for traffic facilities, home or company which is composed of CCD camera, lens, frame grabber, illumination-reflectance decomposition unit, illumination variation detection unit and motion detection unit. The frame grabber accompanies with the CCD camera and lens to take digital images continuously. Then the illumination-reflectance decomposition unit decomposes the captured digital image and transfers it into the illumination and reflectance spectrum to provide the illumination detection unit to analyze the illumination spectrum variation between two adjacent image frames and thus this spectrum variation is used to control the amplification or reduction of the iris; beside ,an object movement detection unit is provided to analyze the illumination variation of two adjacent films to judge if the object in the frame is moving .

In a coding procedure, coding parameters are selected for coding the speech signal to achieve enhanced perceptual quality of reproduced speech. At least one coding parameter value or preferential coding parameter value is selected to make a spectral response of the speech signal more uniform to compensate for spectral variations that might otherwise be imparted into the speech signal by a communications network associated with the signal processing system.

A method and apparatus are provided for noninvasive sampling. More particularly, the method and apparatus relate to control of motion of an optical sample probe interface relative to a tissue sample site. A dynamic probe interface, is used to collect spectra of a targeted sample, control positioning of the sample probe relative to the tissue sample in terms of at least one of x-, y-, and z-axes, and / or control of sample tissue displacement to minimize spectral variations resulting from the sampling process and increase analyte property estimation precision and accuracy.

The present invention provides a method and an apparatus for the in vivo, non-invasive, early detection of alterations and mapping of the grade of these alterations, caused in the biochemical and / or in the functional characteristics of epithelial tissues during the development of tissue atypias, dysplasias, neoplasias and cancers. The method is based, at least in part, on the simultaneous measurement of the spatial, temporal and spectral alterations in the characteristics of the light that is re-emitted from the tissue under examination, as a result of a combined tissue excitation with light and special chemical agents. The topical or systematic administration of these agents result in an evanescent contrast enhancement between normal and abnormal areas of tissue. The apparatus enables the capturing of temporally successive imaging in one or more spectral bands simultaneously. Based on the measured data, the characteristic curves that express the agent-tissue interaction kinetics, as well as numerical parameters derived from these data, are determined in any spatial point of the examined area. Mapping and characterization of the lesion, are based on these parameters.

The invention discloses a fiber Bragg grating sensor-based local crack real-time monitoring method, and belongs to the technical field of structure healthiness monitoring. Strain distribution of the tip of a crack has an obvious non-uniform characteristic, so when a fiber Bragg grating sensor undergoes non-uniform strain in the grid length direction, the shape and the position of a reflection spectrum change. When the strain gradient is different, the spectrum change degree is different. A structure position to be monitored is simplified, finite element analysis is carried out to obtain the strain distribution under different crack lengths in order to determine the layout of the sensor, the characteristic parameter of the reflection spectrum change is extracted, and a quantitative relationship between the characteristic parameter and the crack length is established in order to realize real-time monitoring of the crack in a limit length range. A plurality of sensors are arranged along the crack expansion direction, and a distance between adjacent sensors is smaller than or equal to the effective detection range of the next sensor, so the real-time monitoring of the crack with any prescribed length can be realized.

A signal processing system is well suited for conditioning a speech signal prior to coding the speech signal to achieve enhanced perceptual quality of reproduced speech. The signal processing system may be incorporated into mobile or portable wireless communications devices, wireless infrastructure equipment, or both. The signal processing system includes a filtering arrangement for filtering an input speech signal to make a spectral response of the speech signal more uniform to compensate for spectral variations that might otherwise be imparted into the speech signal by a communications network associated with the signal processing system.

A biological or chemical optical sensing device comprises at least one planar micro-resonator structure included in a light emitting waveguide, and at least one biological or chemical probe bound to at least a part of the micro-resonator structure, the probe operative to bind specifically and selectively to a respective target substance, whereby the specific and selective binding results in a parameter change in light emitted from the waveguide. In one embodiment, the micro-resonator is linear. In some embodiments, the sensing device is active, the waveguide including at least one photoluminescent material operative to be remotely pumped by a remote optical source, and the parameter change, which may include a spectral change or a quality-factor change, may be remotely read by an optical reader.

A method of automatically compensating a multi- or hyper-spectral, multi-pixel image for atmospheric effects, comprising resolving a plurality of spectrally-diverse pixels from the image, determining a spectral baseline from the spectrally-diverse pixels, determining a statistical spectral deviation of the spectrally-diverse pixels, normalizing the statistical spectral deviation by applying a scale factor, and compensating image pixels with both the spectral baseline and the normalized spectral deviation. Another embodiment features a method of automatically determining a measure of atmospheric aerosol optical properties using a multi- or hyper-spectral, multi-pixel image, comprising resolving a plurality of spectrally-diverse pixels from the image, determining a statistical spectral deviation of the spectrally-diverse pixels, correcting the statistical spectral deviation for non-aerosol transmittance losses, and deriving from the statistical spectral deviation one or more wavelength-dependent aerosol optical depths. A final embodiment features a method of automatically determining a measure of atmospheric gaseous optical properties using a multi- or hyper-spectral, multi-pixel image, comprising resolving a plurality of spectrally-diverse pixels from the image, determining a statistical spectral deviation of the spectrally-diverse pixels, and deriving from the statistical spectral deviation wavelength-dependent gaseous optical depths.

Methods and systems for controlling a prosthesis using a brain imager that images a localized portion of the brain are provided according to one embodiment of the invention. The brain imager provides motor cortex activation data by illuminating the motor cortex with near infrared light (NIR) and detecting the spectral changes of the NIR light as passes through the brain. These spectral changes can be correlated with brain activity related to limbic control and may be provided to a neural network, for example, a fuzzy neural network that maps brain activity data to limbic control data. The limbic control data may then be used to control a prosthetic limb. Other embodiments of the invention include fiber optics that provide light to and receive light from the surface of the scalp through hair.

A method for optically analyzing blood vessel walls comprises receiving optical signals from the vessel walls and resolving a spectrum of optical signals in wavelength to generate spectral data. The spectral data is then transformed into the frequency domain. In the preferred embodiment, this transformation is achieved by applying wavelet decomposition. In other embodiments other transform techniques such as Fourier analysis is applied. The spectral data in the frequency domain are then used to analyze the vessel walls. In the typical embodiment, the spectral data are used to analyze a disease state of blood vessels walls such as the presence of atherosclerotic plaques, and their state. Dual domain method enables the spectral signals from blood vessels to be analyzed simultaneously according to frequency and wavelength (time). Dual-Domain Regression Analysis (DRDA) and Dual-Domain Discrimination Analysis (DDDA) in combination with wavelet transform (WT) enable the modeling of signals simultaneously in both domains. This provides a mechanism for isolating the non-interesting variation in spectra, making the system and analysis method more robust against variations in instrument and environmental conditions, e.g., broad-band spectral variation contributed from water, heart motion, and other non-interesting interferences. This provides higher sensitivity and specificity when compared with other models currently being used.

Spectral variation contributed from the absorbance of unwanted correlated signals, such as blood at variable pathlengths between an in vivo catheter optic probe and a coronary vessel wall is an obstacle in the detection of vulnerable plaque. Preprocessing methods are described to reduce the impact of blood upon the spectral signal, based on the principles of Orthogonal Subspace Projection (OSP) and Generalized Least Square (GLS). The multivariate discrimination models used on the processed spectral information reduce the number of independent factors that include contributions from blood. The disclosed chemometric processing including preprocessing methods provide for in vivo spectral detection of medical analytes within the human body and in particular within the coronary vessel wall. A demonstration of how the preprocessing methods impact a discrimination modeling technique is provided, how the blood filters were developed and optimized, and finally how the OSP and GLS blood filters correct the spectral signal and improve the discrimination results of the models.

In a method and apparatus for identifying and distinguishing fungal species, a hyperspectral imaging scanner is used to acquire hyperspectral image data for radiation obtained from a sample area in which at least one unknown fungal species is present. A computer compares the acquired hyperspectral image data with spectral signature data stored in a digital library, which includes spectral signature data for each one of a group of known fungal species, and identifies the fungal species, based on the result of such comparison. The spectral signature data stored in the digital library take into account, for each fungal species, spectral variations that can occur due to at least one of environmental and temporal influences. The computer comparison includes a pixel-by-pixel analysis of the degree of difference between acquired hyperspectral image data and the spectral signature data, so that a spatial distribution of identified fungal species can be determined for a sample area.

An instrument to detect the presence of live microorganisms is described. The instrument is capable of providing simultaneous optical readings of multiple test vials containing different samples. Spectral variations due to metabolic activity of microorganisms are continuously recorded. An automated calibration scheme compensates for the parametric differences among the test vial locations.

A biological or chemical optical sensing device comprises at least one planar micro-resonator structure included in a light emitting waveguide, and at least one biological or chemical probe bound to at least a part of the micro-resonator structure, the probe operative to bind specifically and selectively to a respective target substance, whereby the specific and selective binding results in a parameter change in light emitted from the waveguide. In one embodiment, the micro-resonator is linear. In some embodiments, the sensing device is active, the waveguide including at least one photoluminescent material operative to be remotely pumped by a remote optical source, and the parameter change, which may include a spectral change or a quality-factor change, may be remotely read by an optical reader.

There is provided a method and an apparatus for determining quality parameters on a polarization-multiplexed optical signal based on an analysis of the power spectral density of the Signal-Under-Test (SUT). The method is predicated upon knowledge of the spectral shape of the signal in the absence of significant noise or spectral deformation. This knowledge is provided by a reference optical spectrum trace. Based on this knowledge and under the assumption that ASE noise level is approximately constant in wavelength over a given spectral range, the spectral deformation of the signal contribution of the SUT may be estimated using a comparison of the spectral variations of the optical spectrum trace of the SUT with that of the reference optical spectrum trace.

The invention belongs to the technical field of remote sensing image processing, in particular to a nonlinear de-mixing method for hyperspectral images considering spectral variability. At first, original data are mapped to a high-dimensional characteristic space by a kernel method, and the spectral variation coefficient is considered in the high-dimensional space to perform linear unmixing; at the same time, according to the spatial continuity of object distribution, local smoothing constraint is added to abundance and coefficient of variation, which makes them have spatial smoothness. This method can be used for unsupervised nonlinear spectral unmixing in the presence of spectral variability in Hapke and GBM nonlinear mixing models. The invention can overcome the problem of spectral variability existing in different nonlinear mixing scenes and improve the precision of spectral unmixing, and has important significance in practical application.

A method of and a system for spectral correction in multi-energy computed tomography are provided to correct reconstructed images, including high-energy CT images and Z (effective atomic number) images, for spectral variations, which include time variations on a scanner due to HVPS drift and scanner to scanner variations due to the beamline component differences. The method uses a copper filter mounted on the detector array for tracking the spectral changes. The method comprises: generating copper ratios; computing working air tables; calculating scales and offsets; and correcting high-energy CT images and Z images using calculated scales and offsets. The method further includes an off-line calibration procedure to generate necessary parameters for the online correction.

This invention establishes a mineral identification layer spectrum system which is mineral macro-taxonomy to mineral kind to detail mineral to mineral variation, according to the different grade of characteristic light spectrum parameters in the mineral mixed light spectrum. It concludes and valuates some common light spectrum parameters stability and the relative weigh in the mineral identification and establishes the light spectrum identification method and identification database of the more than twenty kinds of etching minerals. This invention integrates the mineral light spectrum knowledge of professional person into the identification of the mineral based on effectively solving the light spectrum change or variation and makes the general operation person can identify the minerals and realizes the intelligence, batch process and the scale utility of mineral area charting of high light spectrum remote sensor mineral identification.

The present invention provides systems and methods for analyzing the excitation spectra of fluorescent particles in a flowing stream. The system uses a white light laser and color separation optics to provide a spatially-distributed, continuous color-spectrum excitation light system that is used to illuminate a region of a flowing stream. A particle that passes through the detection region traverses the full dispersed spectrum of excitation light, and the fluorescence emissions from the particle are continuously measured as it passes through the detection region. The measured fluorescence emissions at each wavelength of excitation light, which changes through full spectrum of the excitation light as the particle passes through the detection region, provides the excitation spectrum of the particle.

This disclosure describes an apparatus and method of multi-spectral imaging to obtain and analyze information contained in the spectral distribution (reflection, absorption, or emission) of components within the image. The spectral information is captured in a series of images from differing spectral regions. This series of images are then combined into a composite image using re-colorization and image stabilization algorithms for display in real time. The process can be repeated continuously allowing spectral changes over time to be captured and analyzed. In the alternative one sequence of images can be captured for use as a still image.