Method and system to enhance medical signals for real-time analysis and high-resolution display

• US 5,490,516 A
• Filed: 05/06/1993
• Issued: 02/13/1996
• Est. Priority Date: 12/14/1990
• Status: Expired due to Fees

• Current Assignee: William H. Hutson
• Original Assignee: William H. Hutson
• Inventors: Hutson, William H.
• Primary Examiner(s): Kamm, William E.
• Assistant Examiner(s): Getzow, Scott M.
• Application Number:
  US08/058,571
• Time in Patent Office: 1,013 Days
• Field of Search: 128/696, 128/698, 128/699, 128/708, 128/901, 364/413.06
• US Class Current: 600/508
• CPC Class Codes: G01S 15/899 Combination of imaging systems with ancillary equipment
• CPC Class Codes: G01S 3/802 Systems for determining direction or deviation from predetermined direction
• CPC Class Codes: G01S 7/20 Stereoscopic displays; Three-dimensional displays; Pseudo-three-dimensional displays
• CPC Class Codes: G01S 7/6245 Stereoscopic displays; Three-dimensional displays; Pseudo-three dimensional displays
• CPC Class Codes: G06F 17/16 Matrix or vector computation , e.g. matrix-matrix or matrix-vector multiplication, matrix factorization matrix transposition G06F7/78
• CPC Class Codes: G06F 2218/02 Preprocessing
• CPC Class Codes: G06F 2218/08 Feature extraction
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: Y10S 128/901 Suppression of noise in electric signal

Abstract

A medical processing and display system that may be used with a medical monitoring device. This system enhances the medical data it receives. Once received, the medical data is reformatted into a two-dimensional matrix, X. A history database and other information are concatenated with the two-dimensional matrix. The concatenated matrix is decomposed using singular value decomposition ("SVD") to obtain corresponding left and right singular vectors, L and R, respectively, and singular values D. Selected singular vectors are transformed to their autocorrelation matrix form, which are concatenated, then decomposed using SVD to their corresponding singular vectors P, P^t, and singular values D. Certain of the singular vectors P are selected to filter out signal components of interest. The singular values D of the autocorrelation matrix are modified and used to adjust the weights of the associated singular vectors P. The weighted singular vectors are then combined and the resulting coefficients are used as a FIR filter to enhance the original singular vectors L and/or R^t to enhance singular values L_e, R_e. Enhanced medical data containing the features of interest X_e is generated from the enhanced original matrix singular values L_e and R_e, and modified singular values D_e, and the results may be displayed to a diagnotician in various formats.

Claims

1. A method of enhancing medical signals received from a monitoring device comprising the steps of:

inputting medical signals;

extracting data from said medical signals;

embedding said data into a data matrix;

compressing said data matrix into a compressed-data-form;

formatting a portion of said compressed-data-form into at least one auto-correlation matrix;

determining the structural characteristics of each said autocorrelation matrix;

filtering said compressed-data-form based on said structural characteristics to form a filtered compressed-data-form; and

expanding selected data values in said filtered compressed-data-form to result in enhanced data.

2. The method of claim 1, further comprising the step of displaying said enhanced data on a display screen wherein said display shows features of interest in said medical signal.

3. The method of claim 1, further comprising the step of modifying selected data values in said compressed-data-form.

4. The method of claim 3, said compressing step further including decomposing said data matrix into first singular vectors and first singular values.

5. The method of claim 4, wherein at least one said first singular vector is modified by said modifying step.

6. The method of claim 4, wherein at least one said first singular value is modified by said modifying step.

7. The method of claim 4 wherein said formatting step further includes:

transforming at least one said first singular vector into a set of frequency domain coefficients;

multiplying each said coefficient by a complex conjugate;

transforming each coefficient into a set of time domain coefficients; and

placing said time domain coefficients in a Toeplitz matrix form.

8. The method of claim 7 further comprising weighting said combined selected second singular vectors by said corresponding second singular values.

9. The method of claim 3 wherein said method further includes modifying said data matrix by multiplying at least a portion of said data matrix by a singular vector.

10. The method of claim 3 wherein said method further includes partitioning said compressed-data-form into subspaces.

11. The method of claim 10 wherein said compressed-data-form is partitioned into subspaces on the basis of said singular values.

12. The method of claim 11, said method including the step of saving at least one subspace of said compressed-data-form in a historical database.

13. The method of claim 1, said method including the step of saving at least a portion of said compressed-data-form in a historical database.

14. The method of claim 13, said method including the step of concatenating said historical database with said data matrix before compressing said data matrix.

15. The method of claim 13, said method including the step of concatenating said historical database with said compressed-matrix-form after compressing said data matrix.

16. The method of claim 13 wherein said method further includes modifying said historical database before saving said database.

17. The method of claim 1 including the step of concatenating a medical data model with said data matrix before compressing said data matrix.

18. The method of claim 17 wherein said medical data model comprises compressed data.

19. The method of claim 1 including the step of concatenating a medical data model with said data matrix after compressing said data matrix.

20. The method of claim 19 wherein said medical data model comprises compressed data.

21. The method of claim 1, said compressing step further including decomposing said data matrix into eigenvectors and eigenvalues.

22. The method of claim 1 wherein said method further includes scaling said information in said data matrix by multiplying said information at a selected location in said data matrix by a data coefficient associated with said location.

23. The method of claim 1, said determining step further comprising decomposing said autocorrelation matrix into second singular vectors and second singular values.

24. The method of claim 23 further comprising the step of filtering said first singular vectors by said second singular vectors to result in filtered singular vectors.

25. The method of claim 24, said expanding step further comprising combining selected second singular vectors together to form enhanced singular vectors.

26. A method of compressing and storing medical data for later retrieval, comprising:

inputting medical signals;

extracting data from said medical signals;

embedding said data into a data matrix;

compressing said data matrix into a compressed-data-form;

formatting said data matrix into a compressed-data-form into at least one autocorrelation matrix;

determining the structural characteristics of each said autocorrelation matrix;

filtering said compressed-data-form based on said structural characteristics to form a filtered compressed-data-form;

saving selected data values in said filtered compressed-data-form in a computer-readable format.

27. A system for enhancing medical signals received from a monitoring device comprising:

extractor for extracting data from medical signals;

embedder for embedding said data into a data matrix;

compressor for compressing said data matrix into a first compressed-data-form;

formatter for formatting a portion of said first compressed-data-form into at least one autocorrelation matrix;

means for determining the structural characteristics of each said autocorrelation matrix;

filter for filtering said first compressed-data-form based on said structural characteristics to form a filtered first compressed-data-form; and

expander for expanding selected data values in said filtered first compressed-data-form to result in enhanced data.

28. The system of claim 27, further comprising a display system for displaying said enhanced data with the display system including a display screen that is capable of displaying features of interest in said medical signals.

29. The system of claim 27, further comprising a first modifier for modifying selected data values in first compressed-data-form.

30. The system of claim 29, wherein said compressor further includes a decomposer for a decomposing said data matrix into first singular vectors and first singular values.

31. The system of claim 30, wherein at least one said first singular vector is modified by said modifier first.

32. The system of claim 30, wherein at least one said first singular value is modified by said modifier first.

33. The system of claim 29, wherein said system further includes a third modifier for modifying said data matrix by multiplying at least a portion of said data matrix by a singular vector.

34. The system of claim 29, wherein said system further includes a partitioner for partitioning said first compressed-data-form into subspaces.

35. The system of claim 34, wherein the partitioner partitions said compressed-data-form into subspaces on the basis of said singular values.

36. The system of claim 35, wherein said system includes storage means which stores at least one subspace of said first compressed-data-form in a historical database.

37. The system of claim 27, wherein said system includes storage means which stores at least a portion of said first compressed-data-form in a historical database.

38. The system of claim 37, wherein said system includes concatenating means for concatenating said historical database with said data matrix before the compressor compresses said data matrix.

39. The system of claim 37, said system includes concatenating means for concatenating said historical database with said first compressed-matrix-form after the compressor compresses said data matrix.

40. The system of claim 37 wherein said system further includes a second modifier means said historical database before storing said database.

41. The system of claim 27, wherein the includes concatenating means concatenates a medical data model with said data matrix before the compressor compresses said data matrix.

42. The system of claim 41, wherein said medical data model comprises compressed data.

43. The system of claim 27, wherein the system includes concatenating means which concatenates a medical data model with said data matrix after the compressor compresses said data matrix.

44. The system of claim 43, wherein said medical data model comprises compressed data.

45. The system of claim 27, wherein said compressor further includes a decomposer for decomposing said data matrix into eigenvectors and eigenvalues.

46. The system of claim 27, wherein said system further includes a scalar for scaling said information in said data matrix by multiplying said information at a selected location in said data matrix by a data coefficient associated with said location.

47. The system of claim 27, wherein said means for determining further compresses a decompressor for decomposing said autocorrelation matrix into second singular vectors and second singular values.

48. The system of claim 47, wherein the system further includes second filter means for filtering said first singular vectors by said second singular vectors to result in filtered singular vectors.

49. The system of claim 48, wherein the expander further includes a combiner for combining selected second singular vectors to form enhanced singular vectors.

50. A system for compressing and saving medical data for later retrieval, comprising:

extraction for extracting data from medical signals;

embedder for embedding said data into a data matrix;

compressor for compressing said data matrix into a compressed-data-form;

formatter for formatting a portion of said compressed-data-form into at least one autocorrelation matrix;

means for determining the structural characteristics of each said autocorrelation matrix;

filter for filtering said compressed-data-form based on said structural characteristics to form a filtered compressed-data-form;

storage means for storing selected data values in said filtered compressed-data-form in a computer-readable format.