Patent US5596992A successfully refreshed from Google Patents.
US5596992A
Expired / Lapsed
US
⏱️ 0.0 years remaining
Multivariate classification of infrared spectra of cell and tissue samples
Assignee: National Technology and Engineering Solutions of Sandia LLC
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Filing: 1993-06-30
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Granted: 1997-01-28
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Expires: 2013-06-30
Abstract
Abstract Multivariate classification techniques are applied to spectra from cell and tissue samples irradiated with infrared radiation to determine if the samples are normal or abnormal (cancerous). Mid and near infrared radiation can be used for in vivo and in vitro classifications using at least different wavelengths.
Inventors
- 👤 David M. Haaland
- 👤 Howland D. T. Jones
- 👤 Edward V. Thomas
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-24 23:44
CPC Classifications
A; A61; A61B; A61B5/00; A61B5/0059; A61B5/0082; A61B5/0084; A61B5/0086; A61B5/72; A61B5/7235; A61B5/7264; A61B5/0075; A61B5/0088; A61B5/41; A61B5/414; A61B5/415; A61B5/418; A61B5/43; A61B5/4306; A61B5/4318; A61B5/4331; A61B5/4375; A61B5/44; A61B5/441; G; G01; G01N; G01N21/00; G01N21/17; G01N21/25; G01N21/31; G01N21/35; G01N21/359; G16; G16H; G16H50/00; G16H50/20; Y; Y10; Y10S; Y10S977/00; Y10S977/902; Y10S977/932; Y10S977/949
Claims Analysis
Total Claims: 26
Claim 1
Independent Claim
90 words
A method of classifying a cell or tissue sample comprising: generating a plurality of different wavelengths of infrared light; irradiating the sample with the plurality of different wavelengths so that there is differential intensity attenuation caused by variations between different classes of the sample as a function of the different wavelengths; measuring such intensity attenuations to obtain intensity information at at least three different wavelengths; and classifying the sample as one of two or more cell or tissue types from the measured intensity attenuations by using a multivariate classification model.
Claim 2
Independent Claim
90 words
A method of classifying a cell or tissue sample comprising: generating a plurality of different wavelengths of infrared light; irradiating the sample with the plurality of different wavelengths so that there is differential intensity attenuation caused by variations between different classes of the sample as a function of the different wavelengths; measuring such intensity attenuations to obtain intensity information at at least three different wavelengths; and classifying the sample as one of two or more cell or tissue types from the measured intensity attenuations by using a multivariate classification model.
Claim 3
Dependent Claim
16 words
The method of claim 1 wherein the infrared light is in the mid-infrared range of wavelengths.
Claim 4
Dependent Claim
16 words
The method of claim 1 wherein the infrared light is in the near-infrared range of wavelengths.
Claim 5
Dependent Claim
14 words
The method of claim 1 wherein the sample is classified as normal or abnormal.
Claim 6
Dependent Claim
16 words
The method of claim 1 wherein the sample is classified as normal, hyperplastic, dysplastic or neoplastic.
Claim 7
Dependent Claim
15 words
The method of claim 1 wherein the irradiating of the sample is done in vitro.
Claim 8
Dependent Claim
23 words
The method of claim 6 wherein the irradiating of the sample further includes the step of presenting the sample as a monocellular layer.
Claim 9
Dependent Claim
25 words
The method of claim 7 wherein the irradiating of the sample further includes the step of presenting the sample by a cytospin cell preparation technique.
Claim 10
Dependent Claim
15 words
The method of claim 1 wherein the irradiating of the sample is done in vivo.
Claim 11
Dependent Claim
19 words
The method of claim 1 wherein the classifying of the samples includes at least one spectral data pre-processing step.
Claim 12
Dependent Claim
49 words
The method of claim 10 wherein the pre-processing includes at least one of the steps of selecting wavelengths, subtracting a water vapor spectrum, correcting for a linear baseline, and normalizing a spectral region surrounding the different wavelengths, used for classification to one maximum absorption band in that spectral region.
Claim 13
Dependent Claim
25 words
The method of claim 11 further including the step of selecting the maximum absorption band in that spectral region as the one maximum absorption band.
Claim 14
Dependent Claim
17 words
The method of claim 1 wherein the multivariate classification is done by a partial least squares technique.
Claim 15
Dependent Claim
17 words
The method of claim 1 wherein the multivariate classification is done by a principal component regression technique.
Claim 16
Dependent Claim
17 words
The method of claim 1 wherein the multivariate classification is done by a linear discriminant analysis technique.
Claim 17
Dependent Claim
23 words
The method of claim 15 wherein the linear discriminant analysis is preceded by principal component analysis step limiting the number of discriminant variables.
Claim 18
Independent Claim
158 words
A method of classifying a cell or tissue sample comprising: generating a plurality of different wavelengths of mid-infrared light; irradiating the sample with the plurality of different wavelengths so that there is differential intensity attenuation caused by variations between different classes of the sample as a function of the different wavelengths; measuring such intensity attenuations to obtain intensity information at at least three different wavelengths; generating at least one multivariate classification model, said model classifying the different classes of the sample as a function of their different attenuation characteristics at the at least three different wavelengths in relation to a reference classification; calculating the classification of the sample from the measured intensity attenuations by using multivariate classification of the intensity attenuations at the at least three different wavelengths based on the classification model; and classifying the sample as one of two or more cell or tissue types from the measured intensity attenuations by using said multivariate classification model.
Claim 19
Independent Claim
158 words
A method of classifying a cell or tissue sample comprising: generating a plurality of different wavelengths of mid-infrared light; irradiating the sample with the plurality of different wavelengths so that there is differential intensity attenuation caused by variations between different classes of the sample as a function of the different wavelengths; measuring such intensity attenuations to obtain intensity information at at least three different wavelengths; generating at least one multivariate classification model, said model classifying the different classes of the sample as a function of their different attenuation characteristics at the at least three different wavelengths in relation to a reference classification; calculating the classification of the sample from the measured intensity attenuations by using multivariate classification of the intensity attenuations at the at least three different wavelengths based on the classification model; and classifying the sample as one of two or more cell or tissue types from the measured intensity attenuations by using said multivariate classification model.
Claim 20
Dependent Claim
12 words
The method of claim 17 further including classifying said sample in vitro.
Claim 21
Dependent Claim
12 words
The method of claim 17 further including classifying said sample in vivo.
Claim 22
Independent Claim
163 words
A system for classifying cell or tissue samples comprising: means for generating a plurality of different wavelengths of infrared light; means for directing at least a portion of the infrared light into the samples; means for collecting at least a portion of the infrared light after it has interacted with the samples; means for measuring an intensity of the collected infrared light at at least three different wavelengths; means, coupled to the measuring means, for storing the measured intensities as a function of the wavelength; means for storing at least one multivariate classification model which contains data indicative of a correct classification of known cell or tissue samples; and processor means coupled to the means for storing the measured intensities and the means for storing the model, the processor means serving as means for calculating the classification of the cell or tissue samples as one of two or more cell or tissue by use of the multivariate classification model and the measured intensities.
Claim 23
Independent Claim
163 words
A system for classifying cell or tissue samples comprising: means for generating a plurality of different wavelengths of infrared light; means for directing at least a portion of the infrared light into the samples; means for collecting at least a portion of the infrared light after it has interacted with the samples; means for measuring an intensity of the collected infrared light at at least three different wavelengths; means, coupled to the measuring means, for storing the measured intensities as a function of the wavelength; means for storing at least one multivariate classification model which contains data indicative of a correct classification of known cell or tissue samples; and processor means coupled to the means for storing the measured intensities and the means for storing the model, the processor means serving as means for calculating the classification of the cell or tissue samples as one of two or more cell or tissue by use of the multivariate classification model and the measured intensities.
Claim 24
Dependent Claim
22 words
The system of claim 20 wherein the means to direct the light and the means to collect the light comprise an endoscope.
Claim 25
Dependent Claim
11 words
The system of claim 20 further includes means to determine outliers.
Claim 26
Dependent Claim
70 words
The method of claim 1 wherein the step of classifying the sample is performed by a multivariate algorithm using the measured intensity information and at least one multivariate classification model which is a function of conventionally determined cell or tissue sample classes from a set of reference samples and a set of spectral intensities as a function of wavelength obtained from irradiating the set of reference samples with infrared light.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2000-01-28 | 2000-07-29 | 2001-01-28 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2004-01-28 | 2004-07-29 | 2005-01-28 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2008-01-28 | 2008-07-29 | 2009-01-28 | $7700.00 | Window Closed / Lapsed |