Claims Analysis
Total Claims: 19
Claim 1
Independent Claim
111 words
In a processor for color flow imaging of the velocity of blood flowing past adjacent tissue, comprising a wall estimate path circuit and a flow estimate path, and having a nonadaptive mode in which said wall estimate path circuit is bypassed and an adaptive mode in which the estimated wall velocity of said adjacent tissue is mixed with I and Q input data in a complex mixer in said wall estimate path circuit and then output to a wall filter in said flow estimate path circuit, the improvement wherein a fuzzy logic processor in said wall estimate path circuit for determining which of said adaptive and nonadaptive modes shall be operative.
Claim 2
Dependent Claim
111 words
In a processor for color flow imaging of the velocity of blood flowing past adjacent tissue, comprising a wall estimate path circuit and a flow estimate path, and having a nonadaptive mode in which said wall estimate path circuit is bypassed and an adaptive mode in which the estimated wall velocity of said adjacent tissue is mixed with I and Q input data in a complex mixer in said wall estimate path circuit and then output to a wall filter in said flow estimate path circuit, the improvement wherein a fuzzy logic processor in said wall estimate path circuit for determining which of said adaptive and nonadaptive modes shall be operative.
Claim 3
Dependent Claim
45 words
The color flow processor as defined in claim 1, wherein said wall estimate path circuit further comprises an autocorrelator connected to a wall velocity estimator for outputting a value corresponding to the estimated wall velocity to said complex mixer and to said fuzzy logic processor.
Claim 4
Dependent Claim
40 words
The color flow processor as defined in claim 2, wherein said fuzzy logic processor comprises first crisp-to-fuzzy transform means for mapping actual values of estimated wall velocity to a degree of membership in at least one wall velocity fuzzy set.
Claim 5
Dependent Claim
62 words
The color flow processor as defined in claim 2, wherein said wall estimate path circuit further comprises a turbulence estimator connected to receive a value corresponding to estimated wall power from said autocorrelator, to receive a value corresponding to estimated wall variance from said wall velocity estimator, and to output a value corresponding to estimated wall variance to said fuzzy logic processor.
Claim 6
Dependent Claim
66 words
The color flow processor as defined in claim 4, wherein said fuzzy logic processor comprises first crisp-to-fuzzy transform means for mapping actual values of estimated wall velocity to a degree of membership in at least one wall velocity fuzzy set, and second crisp-to-fuzzy transform means for mapping actual values of estimated wall variance to a degree of membership in at least one wall variance fuzzy set.
Claim 7
Dependent Claim
28 words
The color flow processor as defined in claim 4, wherein said fuzzy logic processor is connected to receive said value corresponding to estimated wall power from said autocorrelator.
Claim 8
Dependent Claim
91 words
The color flow processor as defined in claim 6, wherein said fuzzy logic processor comprises first crisp-to-fuzzy transform means for mapping actual values of estimated wall velocity to a degree of membership in at least one wall velocity fuzzy set, second crisp-to-fuzzy transform means for mapping actual values of estimated wall variance to a degree of membership in at least one wall variance fuzzy set, and third crisp-to-fuzzy transform means for mapping actual values of estimated wall power to a degree of membership in at least one wall power fuzzy set.
Claim 9
Dependent Claim
62 words
The color flow processor as defined in claim 7, wherein said fuzzy logic processor further comprises fuzzy-to-crisp transform means for outputting a wallness signal which controls whether estimated wall velocity values will be mixed with said I and Q input data in said complex mixer, said wallness signal being a function of said values corresponding to estimated wall velocity, variance and power.
Claim 10
Dependent Claim
32 words
The color flow processor as defined in claim 8, wherein said fuzzy logic processor further comprises inference means for outputting said wallness signal in accordance with a set of fuzzy logic rules.
Claim 11
Dependent Claim
69 words
The color flow processor as defined in claim 9, wherein said fuzzy logic rules include the rule that if the wall velocity is LOW and the wall variance is LOW and the wall power is HIGH, than wallness is HIGH, where LOW and HIGH are fuzzy values, said adaptive mode being turned ON in response to said HIGH wallness having a degree of membership greater than a predetermined threshold.
Claim 12
Independent Claim
138 words
A method for color flow imaging of the velocity of blood flowing past adjacent tissue, comprising the steps of: acquiring I and Q input data; estimating the wall velocity of said adjacent tissue from said I and Q input data; mixing said estimated wall velocity with said I and Q input data in response to said I and Q input data forming a set of data which is a member of a predetermined class of data sets; mixing a zero wall velocity with said I and Q input data in response to said I and Q input data forming a set of data which is not a member of said predetermined class of data sets; and determining whether said I and Q input data is a member of said predetermined class of data sets using fuzzy logic processing.
Claim 13
Independent Claim
138 words
A method for color flow imaging of the velocity of blood flowing past adjacent tissue, comprising the steps of: acquiring I and Q input data; estimating the wall velocity of said adjacent tissue from said I and Q input data; mixing said estimated wall velocity with said I and Q input data in response to said I and Q input data forming a set of data which is a member of a predetermined class of data sets; mixing a zero wall velocity with said I and Q input data in response to said I and Q input data forming a set of data which is not a member of said predetermined class of data sets; and determining whether said I and Q input data is a member of said predetermined class of data sets using fuzzy logic processing.
Claim 14
Dependent Claim
34 words
The method as defined in claim 11, wherein said fuzzy logic processing comprises the step of transforming said estimated wall velocity to a degree of membership in at least one wall velocity fuzzy set.
Claim 15
Dependent Claim
73 words
The method as defined in claim 11, further comprising the step of estimating the wall variance of said adjacent tissue from said I and Q input data, wherein said fuzzy logic processing comprises the steps of transforming said estimated wall velocity to a degree of membership in at least one wall velocity fuzzy set and transforming said estimated wall variance to a degree of membership in at least one wall variance fuzzy set.
Claim 16
Dependent Claim
94 words
The method as defined in claim 11, further comprising the steps of estimating the wall variance and wall power of said adjacent tissue from said I and Q input data, wherein said fuzzy logic processing comprises the steps of transforming said estimated wall velocity to a degree of membership in at least one wall velocity fuzzy set, transforming said estimated wall variance to a degree of membership in at least one wall variance fuzzy set and transforming said estimated wall power to a degree of membership in at least one wall power fuzzy set.
Claim 17
Dependent Claim
56 words
The method as defined in claim 14, wherein said fuzzy logic processing further comprises the steps of outputting a wallness signal which controls whether estimated wall velocity will be mixed with said I and Q input data, said wallness signal being output as a function of said values corresponding to estimated wall velocity, variance and power.
Claim 18
Dependent Claim
30 words
The method as defined in claim 15, wherein said fuzzy logic processing further comprises the step of outputting said wallness signal in accordance with a set of fuzzy logic rules.
Claim 19
Dependent Claim
67 words
The method as defined in claim 16, wherein said fuzzy logic rules include the rule that if the wall velocity is LOW and the wall variance is LOW and the wall power is HIGH, than wallness is HIGH, where LOW and HIGH are fuzzy values, said adaptive mode being turned ON in response to said HIGH wallness having a degree of membership greater than a predetermined threshold.