Living body internal active source estimation apparatus

Surgery – Diagnostic testing – Detecting nuclear – electromagnetic – or ultrasonic radiation

Reexamination Certificate

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Details

C600S409000, C600S524000, C324S307000, C324S308000, C324S309000, C324S200000, C324S210000, C324S212000

Reexamination Certificate

active

06226544

ABSTRACT:

BACKGROUND OF THE INVENTION
The present invention relates to a living body internal active source estimation apparatus for estimating positions and moments of active sources in a living body on the basis of electromagnetic field distribution observed on the living body surface.
Heretofore, when estimating active sources in a living body on the basis of electromagnetic distribution observed on the living body surface, current dipoles were used in substitution for main active sources in the brain, and the positions and the moments of the dipoles were estimated. The estimation of the positions and the moments of the dipoles from the observed electromagnetic field distribution, was executed by, for instance, a method as described in the following.
An electromagnetic model of a living body is used, and it is assumed that dipoles are generated in the living body. With these dipoles, an electromagnetic field distribution, which would be recorded at an observation point placed on a surface, is calculated.
Then, denoting the calculated value of the electromagnetic field distribution at i-th observation point by ø
i
(dip)
and an observed value obtained by actual measurement by ø
i
(mes)
, the sum of squares of the residuals r, for instance, is calculated as a residual function of these values expressed as:
r
=

i

(
φ
i
(
mes
)
-
φ
i
(
dip
)
)
2
.
(
1
)
If the sum of squares of the residuals r is greater than a predetermined value, the positions and moments of the dipoles are corrected by using an optimization method based on numerical analysis, typically a Marquardt method or a Simplex Method, for reducing the sum of squares of the residuals r.
When dipole positions and moments are obtained such that they reduce the sum of squares of the residuals r to be less than the predetermined value, they are executed to be a result of estimation.
The above method is described in detail in Bin He et al., “Electric Dipole Tracing in the Brain by Means of the Boundary Element Method and Its Accuracy”, IEEE dTransactions on Biomedical Engineering, Vol., BME-34., No. 6, June 1978 (hereinafter referred to as Literature 1).
An estimation method based on a regional dipole source model, is carried out by assuming a relatively large number of dipoles in a living body and fixing the positions and moments of these dipoles for estimating only the size of these dipoles.
In this method, denoting the dipole size to be estimated by q
j
, by using a matrix F which is calculated from an electromagnetic model of the living body and the positions and directions of the dipoles, the observed value ø
i
(mes)
is expressed as:
φ
i
(
mes
)
=

j
m

F
ij

q
j
.
(
2
)
Usually, the number of dipoles is greater than that of observed data. Thus, it is possible to estimate dipole size qi by obtaining the generalized inverse matrix F+ of the matrix F. This estimated dipole size is given as:
q=F
+
ø
(mes)
.  (3)
The above method is detailed in J. Z. Wang et al., “Magnetic Source Image Determined by a Lead-Field Analysis: The Unique Minimum-Norm Least-Squares Estimation”, IEEE Transactions on Biomedical Engineering, Vol. BME-39, No. 7, July 1992 (hereinafter referred to as Literature 2).
The above prior art techniques, however, have the following problems.
(1) In the above method for estimating the positions and the moments of dipoles, it is necessary to repeatedly carry out the calculation a large number of times. Therefore, extremely long time should be spent until obtaining the final positions and moments of dipoles. In addition, increase of the number of assumed dipoles leads to enormous time required for the estimation. Besides, since an activity at a certain point is assumed to be a dipole, it is impossible to obtain optimal solutions for an active source having certain region.
(2) In the method using a regional dipole source model, if the observed data contains even slight noise, the data corresponding to the noise is greatly reflected on the estimation result, resulting in deterioration or loss of reliability.
SUMMARY OF THE INVENTION
The present invention was made in view of the above problems inherent in the prior art, and has an object of providing a living body internal active source estimation apparatus, which permits fast dipole size estimation with less noise influence by using a regional dipole source model.
According to an aspect of the present invention, there is provided a living body internal active source estimation apparatus for estimating positions and moments of internal active sources in a living body on the basis of electromagnetic field distribution observed on the living body surface comprising: a forward problem matrix transformation means for receiving living body model data, regional dipole position/direction data and measurement position data and (calculating and providing a forward problem matrix on the basis of the input data; a coupling coefficient/threshold calculating means for receiving electromagnetic field distribution measurement data and the forward problem matrix and calculating coupling coefficients and thresholds on the basis of the electromagnetic field distribution measurement data and the forward problem matrix; an artificial neural network means for estimating sizes of regional dipoles by using an artificial neural network having coupling coefficients representing coupling states among a plurality of units and thresholds thereof; and an estimation result output means for converting unit output data from the artificial neural network means to a result of estimation and providing the result; the artificial neural network means including: a coupling coefficient memory means for storing the coupling coefficients representing the coupling states among the units; a threshold storing means for storing the thresholds of the units; a unit output storing means for storing the unit output data; and a unit output updating means for selecting units as subject of output updating, receiving the coupling coefficients provided from the coupling coefficient storing means and the unit output data provided from the unit output storing means, updating the unit output data by updating thereof and calculating network energy from the coupling coefficients and the unit output data; the unit output data being made to be the estimation result when the rate of reduction of the network energy becomes lower than a predetermined rate.
The living body internal active source estimation apparatus further comprises: a total activity calculating means for receiving the electromagnetic field distribution measurement data and calculating internal total activity in the living body on the basis of the received electromagnetic field distribution measurement data, a spatial activity restriction calculating means for receiving regional dipole position/direction data and spatial restriction data and providing a matrix restricting the regional dipole activity size on the basis of the input data, or a generalized inverse matrix calculating means for receiving the electromagnetic field distribution measurement data and a forward problem matrix provided from the forward problem matrix converting means and calculating a generalized inverse matrix on the basis of the input data.
According to another aspect of the present invention, there is provided a living body internal active source estimation method for estimating positions and moments of active sources in a living body on the basis of electromagnetic field distribution observed on the living body surface comprising steps of: calculating a forward problem matrix on the basis of living body model data, regional dipole position/direction data and measurement position data; calculating coupling coefficients and thresholds on the basis of specified data including electromagnetic field distribution measurement data and the forward problem matrix; estimating sizes of regional dipoles by using an artificial neural network having coupling coefficients representing coupling states among a plurality of units and thresholds

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