Ultrasonic living body tissue characterization system

• US 4,575,799 A
• Filed: 03/23/1983
• Issued: 03/11/1986
• Est. Priority Date: 03/23/1983
• Status: Expired due to Fees

• Current Assignee: Fujitsu Limited
• Original Assignee: Fujitsu Limited
• Inventors: Miwa, Hirohide, Reid, John M.
• Primary Examiner(s): Smith, Jerry
• Assistant Examiner(s): Jablon, Clark A.
• Application Number:
  US06/477,935
• Time in Patent Office: 1,084 Days
• Field of Search: 73/599, 73/602, 73/614, 73/620, 73/624, 73/625, 73/627, 73/629, 128/660, 364/414
• US Class Current: 600/442
• CPC Class Codes: G01S 15/8954 using a broad-band spectrum
• CPC Class Codes: G01S 7/52025 for pulse systems G01S7/52034 takes precedence
• CPC Class Codes: G01S 7/52036 using analysis of echo signal for target characterisation

Abstract

A method for ultrasonic living body tissue characterization using a transducer and processor. The method includes the steps of transmitting an ultrasonic pulse into the tissue and receiving a reflected pulse, calculating the normalized power frequency spectrum of the reflected pulse, determining the frequency at which the maximum value for the power spectrum occurs, determining the high and low half power frequencies, calculating the upper and lower frequency ratios of the maximum value frequency and the half power frequencies, and determining the power exponent of the frequency of the reflection coefficient. The frequency exponent of the reflection coefficient is used to calculate the attenuation slope of the ultrasonic wave. The attenuation slope or the reflection power exponent is used to generate a tomographic image of the living tissue characteristics for visual non-invasive tissue diagnosis. The attenuation slope and/or the reflection power exponent tomographic image or the others can be combined with a reflection intensity tomographic image or the others to produce other diagnostic images.

Claims

1. An ultrasonic living body tissue characterization method, comprising the steps of:

(a) transmitting an ultrasonic pulse into the body tissue, receiving an echo reflected from within the body tissue and producing an echo signal from the echo;

(b) converting a portion of the echo signal corresponding to a depth z into a power spectrum;

(c) deriving a tissue power transfer function, R(f), of the portion utilizing a reference power spectrum obtained at the depth z in a reference medium where f indicates frequency within the spectrum;

(d) finding a maximum, Rm, of the tissue power transfer function R(f) and a frequency, fm, at which the maximum Rm occurs;

(e) normalizing the tissue power transfer function R(f) with the maximum Rm;

(f) producing a normalized frequency y in accordance with y=f/fm and substituting the normalized frequency, y, for the frequency f; and

(g) extracting a reflection power exponent, n, from the shape of the normalized tissue power transfer function R(f)/Rm as a function of the normalized frequency y and the reflection power exponent n.

2. A method as recited in claim 1, further comprising the step of (h) producing an attenuation slope β

using the reflection power exponent n.

3. A method as recited in claim 2, wherein step (g) comprises the steps of:

(g1) determining a high fraction frequency f+ higher than fm at which the value of the normalized tissue power transfer function is a fraction of the maximum Rm;

(g2) producing a low fraction frequency f- lower than fm at which the value of the normalized tissue power transfer function is the fraction of the maximum Rm;

(g3) calculating an upper frequency ratio y+ dependent on fm and f+;

(g4) computing a lower frequency ratio y- dependent on fm and f-; and

(g5) determining the reflection power exponent n in dependence on y+ and y-.

4. A method as recited in claim 3, wherein step (g5) performs

5. A method as recited in claim 4, wherein y+=f+/fm and y-=f-/fm.

6. A method as recited in claim 5, wherein the tissue being characterized has tissue regions numbered 1 to i, wherein i is a positive integer, and further comprising the step of (i) calculating at least one of an attenuation slope β

i and β

(z) for each tissue region from one of ##EQU10## where Δ

T is the time difference between the echos from the boundaries i+1, i and i, i-1, and C is the velocity of sound in the living body tissue.

7. A method as recited in claim 6, wherein the fraction is equal to one-half.

8. A method as recited in claim 7, further comprising the steps of:

(j) calculating a linear integration of β

along a path from n; and

(k) producing one of a β and

n image using a computer tomography image reconstruction algorithm on the linear integrations for various projections.

9. A method as recited in claim 7, wherein pulses are transmitted into the body tissue and reflected echos received a plurality of times from different locations of the living body, and said method further comprises the step of (l) generating at least one of an attenuation slope β

i and a reflection power exponent ni tomographic image representing one of an attenuation slope and reflection power exponent diagnostic image used for living body tissue diagnosis.

10. A method as recited in claim 9, wherein each reflected echo has a reflection intensity, and wherein said method further comprises the steps of:

(m) generating a reflection intensity tomographic image in dependence upon the reflection intensity of the reflected echo; and

(n) combining the reflection intensity tomographic image with at least one of the attenuation slope β

i and the reflection power exponent ni tomographic image.

11. A method as recited in claim 10, wherein step (b) performs a Fast Fourier transform on the reflected echo.

12. A method as recited in claim 11, wherein step (c) comprises the steps of:

(c1) generating the reference power spectrum; and

(c2) dividing the power spectrum by the reference power spectrum and subtracting a log spectra therefrom.

13. A method as recited in claim 3, using a table for storing values of n for each value of y+-y-, and wherein step (g5) comprises:

(g5i) scanning said table with the value of y+-y-; and

(g5ii) comparing the value with table entries until a match is found, the value of n is the corresponding table entry when a match occurs.

14. A method as recited in claim 13, wherein y+=f+/fm and y-=f-/fm.

15. A method as recited in claim 14, wherein the tissue being characterized has tissue regions numbered 1 to i, where i is a positive integer, and further comprising the step of (i) calculating at least one of an attenuation slope β

i and β

(z) for each tissue region from ##EQU11## wherein Δ

T is the time difference between the echoes from the boundaries i+1, i and i, i-1, and C is the velocity of sound in the living body tissue.

16. A method as recited in claim 15, wherein the fraction is equal to one-half.

17. A method as recited in claim 16, further comprising:

(j) calculating a linear integration of β

along a path from n; and

(k) constructing one of a β and

n image using a computer tomography image reconstruction algorithm on the linear integrations for various projections.

18. A method as recited in claim 16, wherein pulses are transmitted into the body tissue and reflected echos received a plurality of times from different locations of the living body, and further comprising the step of (j) generating at least one of an attenuation slope β

i and reflection power exponent ni tomographic image representing one of an attenuation slope and reflection power exponent diagnostic image used for living body tissue diagnosis.

19. A method as recited in claim 18, wherein each reflected echo has a reflection intensity, and further comprising the steps of:

(k) generating a reflection intensity tomographic image in dependence upon the reflection intensity of the reflected echo; and

(l) combining the reflection intensity tomographic image with one of the attenuation slope β

i and the reflection power exponent ni tomographic image.

20. A method as recited in claim 19, wherein step (b) performs a Fast Fourier Transform on the reflected echo.

21. A method as recited in claim 20, wherein step (c) comprises the steps of:

(c1) generating the reference power spectrum; and

(c2) dividing the power spectrum by the reference power spectrum and subtracting a log spectra.