Computer for evaluating signals from nuclear magnetic resonance tomography and a nuclear resonance tomograph equipped with said computer

• US 6,388,443 B1
• Filed: 07/18/2000
• Issued: 05/14/2002
• Est. Priority Date: 01/23/1998
• Status: Expired due to Term

• Current Assignee: Stefan Posse
• Original Assignee: Forschungszentrum Jã¼Lich GmbH (Bundesrepublik Deutschland)
• Inventors: Taylor, John, Posse, Stefan, Gembris, Daniel
• Primary Examiner(s): Lefkowitz, Edward
• Assistant Examiner(s): Shrivastav, Brij B.
• Application Number:
  US09/618,244
• Time in Patent Office: 665 Days
• Field of Search: 324/312, 324/307, 324/300, 324/322, 600/544, 600/545
• US Class Current: 324/312
• CPC Class Codes: G01R 33/4806 Functional imaging of brain activation
• CPC Class Codes: G01R 33/56 Image enhancement or correction, e.g. subtraction or averaging techniques , e.g. improvement of signal-to-noise ratio and resolution

Abstract

In a computer for evaluating signals from nuclear magnetic resonance tomography and a tomograph using such a computer, the neuronal activity measured during a nuclear magnetic resonance tomographic examination follows a protocol, which reproduces the temporal sequence of stimuli. During a correlation analysis, the sensitivity of known means to changes in the signal-response form normally decreases with each activation cycle. According to the invention, better evaluation results can be achieved in the correlation analysis by using a constant number of n data values in a correlation analysis employing a sliding-window technique. As the data measurement progresses, the oldest value is continuously disposed of and the most recent data value utilized in the calculation.

Claims

1. A computer for the evaluation of data from nuclear spin tomographs employing a correlation analysis which is performed utilizing a detrending procedure, said computer including evaluation means, which, in accordance with a sliding-window procedure, utilize a number of n data values for said correlation analysis, in which, with continuing data measurement, the respective oldest values are discarded and the newest data values are employed in the computation.

2. A computer according to claim 1, wherein the number of n data values utilized for the computation remains constant.

3. A computer according to claim 1, wherein said evaluation means are operative in such a way that the correlation formula $\rho$

=x→

S

r→

S

x→

S





r→

S

is transformed in such a way that at least one sub-expression remains which can be iteratively computed.

4. A computer according to claim 3, wherein evaluation means operate in such a way that the formula $\rho$

=x→

S

r→

S

x→

S





r→

S

is transformed in such a way that only sub-expressions remain, which can be iteratively computed.

5. A computer according to claim 1, wherein said sliding-window means are operative by a sliding-window procedure following the formulae:

$\mathrm{\rho <br><br>}=\frac{\stackrel{\to <br><br>}{x}<br><br>\stackrel{\to <br><br>}{r}-\underset{i}{\sum <br><br>}<br><br>{\mathrm{\delta <br><br>}}_i<br><br>\stackrel{\to <br><br>}{x}<br><br>{\stackrel{\to <br><br>}{s}}_i}{\sqrt{h_1<br><br>h_2}}.$

6. A computer according to claim 1, wherein said evaluation means calculate detrending coefficients in γ

and δ

according to the formulae;

7. A computer according to claim 1, wherein said evaluation means utilize a sliding-window procedure in accordance with the formula:

$\mathrm{\rho <br><br>}=\frac{a-b<br><br>\text{\hspace{1em}<br><br>}<br><br>\frac{c}{N}}{\sqrt{d-\frac{b^2}{N}}<br><br>\sqrt{e-\frac{c^2}{N}}}.$

8. A computer according to claim 5, wherein said evaluation means operate in such a way that a drop of the detrending coefficient resulting from the method is compensated for in an additional computation step.

9. A computer according to claim 8, wherein the evaluation means perform the compensation in accordance with the formula:

${\widetilde{\mathrm{\gamma <br><br>}}}_k=\underset{i\ge <br><br>k}{\overset{L-1}{\sum <br><br>}}<br><br>{\mathrm{\gamma <br><br>}}_i<br><br>\left(\begin{array}{c}i\\ k\end{array}\right)<br><br>t_0^{i-k},$

if polynomial detrending vectors have been chosen.

10. A computer according to claim 1, wherein said evaluation means are adapted to permit calculation with spatially different reference vectors.

11. A computer according to claim 10, wherein said evaluation means are capable of adapting said reference vectors to the time sequences, which have the highest correlation coefficients.

12. A computer according to claim 1, wherein said evaluation means operate in such a way that the reference vectors are optimized based on the initial vectors.

13. A computer according to claim 12, wherein said evaluation means are optimizing said reference vectors in accordance with the formula $T_i=\frac{{\Sigma }_{}}{}$

∀

pixels

(k,l)

p

(k,l)>

t

xi,k,lΣ

∀

pixels

(k,l)

p

(k,l)>

t

1.

14. A nuclear resonance tomograph including a computer for the evaluation of data from nuclear spin tomographs wherein a correlation analysis is performed utilizing a detrending procedure, said computer including evaluation means, which, in accordance with a sliding-window procedure, utilize a number of n data values for said correlation analysis, in which, with continuing data measurement, the respective oldest data values are discarded and the newest data values are employed in the computation.