Method of performing tomographic imaging in a charged-particle microscope

1. A method of performing sub-surface imaging of a specimen in a charged-particle microscope of a scanning transmission type, comprising:

providing a beam of charged particles that is directed from a source along a particle-optical axis through an illuminator so as to irradiate the specimen;

providing a detector for detecting a flux of charged particles traversing the specimen;

causing said beam to follow a scan path across a surface of said specimen, and recording an output of said detector as a function of scan position, thereby acquiring a scanned charged-particle image I of the specimen;

repeating this procedure for different members n of an integer sequence, by choosing a value P n of a variable beam parameter P and acquiring an associated scanned image I n , thereby compiling a measurement set M={(I n , P n )}; and

using computer processing apparatus to automatically deconvolve the measurement set M and spatially resolve it into a result set representing depth-resolved imagery of the specimen,

wherein:

said variable beam parameter P is focus position along said particle-optical axis;

said scanned image I is an integrated vector field image, obtained by;

embodying said detector to comprise a plurality of detection segments;

combining signals from different detection segments so as to produce a vector output from the detector at each scan position, and compiling this data to yield a vector field; and

mathematically processing said vector field by subjecting it to a two-dimensional integration operation.

2. A method according to claim 1 , wherein:

the specimen is conceptually sub-divided into a series [S 1 , . . . , S m ] of m slices disposed along and normal to said particle-optical axis;

for each value of n, the corresponding image I n is expressed as a linear sum Σ j=1 j=m i n (S j ) of discrete sub-images, each associated with a different one of said slices.

3. A method according to claim 2 , wherein:

for each given focus value P n , a particular slice S Bn is associated with a position of best focus within the specimen;

t n (S j ) is set to zero for each integer j≠Bn, so that I n is taken to derive solely from S Bn .

4. A method according to claim 3 , wherein said beam irradiates the specimen with an opening angle of at least 20 milliradians.

5. A method according to claim 1 , wherein said deconvolution is performed using a Source Separation algorithm.

6. A method according to claim 5 , wherein said Source Separation algorithm is selected from the group consisting of Independent Component Analysis, Principal Component Analysis, Non-Negative Matrix Factorization, and combinations and hybrids hereof.

7. A charged-particle microscope of a scanning transmission type comprising:

a specimen holder, for holding a specimen;

a source, for producing a beam of radiation;

an illuminator, for directing said beam so as to irradiate said specimen;

an imaging system, for receiving a flux of charged particles transmitted through the specimen and directing it onto a detector;

deflectors for causing said beam to traverse a scan path relative to a surface of the specimen;

a controller, configured to:

record an output of the detector as a function of scan position, thus producing an image I;

repeat this procedure at a set of different values P n of a variable beam parameter P and storing an associated image I n , thereby compiling a measurement set M={(I n , P n )}, where n is a member of an integer sequence; and

automatically deconvolve the measurement set M and spatially resolving it into a result set representing depth-resolved imagery of the specimen, wherein:

said detector comprises a plurality of detection segments; and

said controller is configured to:

select said variable beam parameter P to be focus position along said particle-optical axis;

combine signals from different detection segments of said detector so as to produce a vector output from the detector at each scan position, and compile this data to yield a vector field; and

mathematically process said vector field by subjecting it to a two-dimensional integration operation, thereby rendering said image I as an integrated vector field image.

8. The method of claim 2 , wherein said deconvolution is performed using a Source Separation algorithm.

9. The method of claim 3 , wherein said deconvolution is performed using a Source Separation algorithm.

10. The method of claim 4 , wherein said deconvolution is performed using a Source Separation algorithm.

11. The apparatus of claim 7 , wherein the controller is further configured to conceptually subdivide the sample into a series [S 1 , . . . , S m ] of m slices disposed along and normal to said particle-optical axis, where for each value of n, the corresponding image I n is expressed as a linear sum Σ j=1 j=m i n (S j ) of discrete sub-images, each associated with a different one of said slices.

12. The apparatus of claim 7 , wherein the controller is further configured to, for each given focus value P n , associate a particular slice S Bn with a position of best focus within the specimen; and

set i n (S j ) to zero for each integer j≠B n , so that I n is taken to derive solely from S Bn .

13. The apparatus of claim 7 , wherein said illuminator directs said beam to irradiate the specimen with an opening angle of at least 20 milliradians.

14. The apparatus of claim 7 , wherein said controller is further configured to perform said deconvolution using a Source Separation algorithm.

15. The apparatus of claim 14 , wherein said Source Separation algorithm is selected from the group consisting of Independent Component Analysis, Principal Component Analysis, Non-Negative Matrix Factorization, and combinations and hybrids hereof.

16. The apparatus of claim 11 , wherein said controller is further configured to perform said deconvolution using a Source Separation algorithm.

17. The apparatus of claim 16 , wherein said Source Separation algorithm is selected from the group consisting of Independent Component Analysis, Principal Component Analysis, Non-Negative Matrix Factorization, and combinations and hybrids hereof.

18. The apparatus of claim 12 , wherein said controller is further configured to perform said deconvolution using a Source Separation algorithm.

19. The apparatus of claim 18 , wherein said Source Separation algorithm is selected from the group consisting of Independent Component Analysis, Principal Component Analysis, Non-Negative Matrix Factorization, and combinations and hybrids hereof.