Computer aided diagnosis of lung disease
AssigneeSavic Research, LLC
InventorMichael Savic
Life of this patent
Estimating the term…
Abstract
A method and apparatus by which lung deceases are identified uses computer analysis of sound signals that are picked up from various locations on the chest walls of a subject by a modified stethoscope. The modification includes a small microphone in one of the hoses of the stethoscope. Signals from the microphone are input to a computer such as a personal computer or PC for processing. The computer extracts from these signals features which are dominant for particular lung diseases. A classifier classifies these features, determines if the lungs are diseased, and identifies the disease.
Claims28
A method of identifying a lung disease that produces sounds that are characteristic of the lung disease, comprising subjecting the sounds to autoregressive modeling to recognize and thus identify the lung disease and projecting at least one two-dimensional representation of autocorrelation coefficients of the autoregressive modeling for the sounds and identifying the disease by selecting at least one pair of coefficients that separate clusters of samples in the representation to identify the lung disease.
A method of identifying a lung disease that produces sounds that are characteristic of the lung disease, comprising subjecting the sounds to autoregressive modeling to recognize and thus identify the lung disease and projecting a plurality of two-dimensional representations of autocorrelation coefficients of the autoregressive modeling for the sounds, selected features of the representations that provide relatively good correlation to the lung disease as compared to feature that give relatively poor correlation to the lung disease, and identifying the disease by selection of at least one pair of coefficients that separate clusters of samples in the representation for the features that provide relatively good correlation to the lung disease.
A method of identifying a lung disease that produces sounds that are characteristic of the lung disease, comprising subjecting the sounds to autoregressive modeling to recognize and thus identify the lung disease and projecting at least one two-dimensional representation of autocorrelation coefficients of the autoregressive modeling for the sounds, subjecting the representation to discriminant analysis to select dominant features of the representation and using neural network analysis of the dominant features for identifying the disease.
A method of identifying a lung disease that produces sounds that are characteristic of the lung disease, comprising subjecting the sounds to autoregressive modeling to recognize and thus identify the lung disease and wherein the use of autoregressive modeling includes extracting a plurality of autocorrelation coefficients from the sounds, subjecting at least some of the coefficients to multi-dimensional projection to extract features of the projection, and using the features to identifying the lung disease.
An apparatus for identifying a lung disease in a subject, the lung disease producing lung sounds that are characteristic of the lung disease, the apparatus comprising:
- a stethoscope for acquiring the lung sounds from the subject;
- a transducer operatively connected to the stethoscope for converting the lung sounds to a signal;
- and a computer-based analyzer for analyzing the signal to identify the lung disease and wherein the computer-based analyzer comprises a computer that is programmed with a program for analyzing the signal to identify the lung disease using autoregressive modeling and wherein the program plots at least one two dimensional representation of autocorrelation coefficients of the autoregressive modeling for the signal and identifies the disease by selection at least one pair of coefficients that separate clusters of samples in the representation.
An apparatus for identifying a lung disease in a subject, the lung disease producing lung sounds that are characteristic of the lung disease, the apparatus comprising:
- a stethoscope for acquiring the lung sounds from the subject;
- a transducer operatively connected to the stethoscope for converting the lung sounds to a signal;
- and a computer-based analyzer for analyzing the signal to identify the lung disease and wherein the computer-based analyzer comprises a computer that is programmed with a program for analyzing the signal to identify the lung disease using autoregressive modeling, wherein the program plots a plurality of two-dimensional representations of autocorrelation coefficients of the autoregressive modeling for the sounds, and selects features of the representations that provide relatively good correlation to the lung disease as compared to feature that give relatively poor correlation to the lung disease, and identifies the disease by selection at least one pair of coefficients that separate clusters of samples in the representation for the features that provide relatively good correlation to the lung disease.
An apparatus for identifying a lung disease in a subject, the lung disease producing lung sounds that are characteristic of the lung disease, the apparatus comprising:
- a stethoscope for acquiring the lung sounds from the subject;
- a transducer operatively connected to the stethoscope for converting the lung sounds to a signal;
- and a computer-based analyzer for analyzing the signal to identify the lung disease and wherein the computer-based analyzer comprises a computer that is programmed with a program for analyzing the signal to identify the lung disease using autoregressive modeling, wherein the program plots at least one two-dimensional representation of autocorrelation coefficients of the autoregressive modeling for the sounds, and subjects the representation to discriminant analysis to select dominant features of the representation, and uses neural network analysis of the dominant features for identifying the disease.
An apparatus for identifying a lung disease in a subject, the lung disease producing lung sounds that are characteristic of the lung disease, the apparatus comprising:
- a stethoscope for acquiring the lung sounds from the subject;
- a transducer operatively connected to the stethoscope for converting the lung sounds to a signal;
- and a computer-based analyzer for analyzing the signal to identify the lung disease, wherein the program extracts a plurality of autocorrelation coefficients from the sounds, subjects at least some of the coefficients to multi-dimensional projection to extract features of the projection, and uses the features to identifying the lung disease.
An apparatus for identifying a disease in a subject, the disease producing sounds that are characteristic of the disease, the apparatus comprising:
- means for acquiring the sounds;
- and a computer-based analyzer for analyzing the sounds to identify the disease using autoregressive modeling, wherein the program projects at least one two-dimensional representation of autocorrelation coefficients of the autoregressive modeling for the sound and identifies the disease by selection of at least one pair of coefficients that separate clusters of samples in the representation.
An apparatus for identifying a disease in a subject, the disease producing sounds that are characteristic of the disease, the apparatus comprising:
- means for acquiring the sounds;
- and a computer-based analyzer for analyzing the sounds to identify the disease using autoregressive modeling, wherein the program plots a plurality of two-dimensional representations of autocorrelation coefficients of the autoregressive modeling for the sounds, and selects features of the representations that provide relatively good correlation to the lung disease as compared to feature that give relatively poor correlation to the lung disease, and identifies the disease by selection of at least one pair of coefficients that separate clusters of samples in the representation for the features that provide relatively good correlation to the disease.
An apparatus for identifying a disease in a subject, the disease producing sounds that are characteristic of the disease, the apparatus comprising:
- means for acquiring the sounds;
- and a computer-based analyzer for analyzing the sounds to identify the disease using autoregressive modeling, wherein the program plots at least one two-dimensional representation of autocorrelation coefficients of the autoregressive modeling for the sounds, and subjects the representation to discriminant analysis to select dominant features of the representation, and uses neural network analysis of the dominant features for identifying the disease.
An apparatus for identifying a disease in a subject, the disease producing sounds that are characteristic of the disease, the apparatus comprising:
- means for acquiring the sounds;
- and a computer-based analyzer for analyzing the sounds to identify the disease using autoregressive modeling, wherein the program extracts a plurality of autocorrelation coefficients from the sounds, subjects at least some of the coefficients to multi-dimensional projection to extract features of the projection, and uses the features to identifying the disease.
Dependencies are inferred from the claim text.