Methods and systems for tomographic microscopy imaging

1 . A method for acquiring tomographic images of a sample in a microscopy system,

wherein the sample comprises a defined region including an exposure region having features that are of interest for imaging, and

wherein the method comprises:

capturing an image of at least a part of the sample; and

determining a location in three-dimensional space of the defined region by:

determining a first configuration, in a projection space, of a first feature of the sample in three-dimensional space relative to a configuration of a second feature of the sample in three-dimensional space,

determining a second configuration of a third feature in the part of the sample in three-dimensional space relative to a configuration of a fourth feature in the part of the sample in three-dimensional space,

comparing the relative configuration of the third feature and the fourth feature in the image of the part of sample to the relative configuration of the first feature and the second feature in the projection space to determine an angle between an axis of the sample and a tilt axis of a stage on which the sample is positioned, and

determining the location in three-dimensional space of the defined region based, at least in part, on the comparison of the relative configuration of the third feature and the fourth feature in the image of the part of the sample to the relative configuration of the first feature and the second feature in the projection space and the determination of the angle between the axis of the sample and the tilt axis of the stage; and

positioning a beam of particles over the exposure region based on the determined location in three-dimensional space of the exposure region.

2 . The method of claim 1 , wherein the method further comprises generating a model of at least a modeled part of the sample, and wherein the determination of the location in three-dimensional space of the defined region is based, at least in part, on the model.

3 . The method of claim 2 , wherein the method comprises

determining a projection of at least a projected part of the sample, wherein the projection is based, at least in part, on the model;

capturing an image of the projected part of the sample;

comparing the image and the projection of the projected part of the sample; and

refining the model based on the comparison between the image and the projection of the projected part of the sample.

4 . The method of claim 2 , wherein the method comprises capturing images at a plurality of sample orientations, and wherein the image of the part of the sample comprises the image of the part of the sample at a first sample orientation.

5 . The method of claim 4 , wherein the method comprises capturing an image of at least the part of the sample at a second sample orientation, wherein the second sample orientation is not identical to the first sample orientation.

6 . The method of claim 5 , wherein the determination of the location in three-dimensional space of the defined region is based, at least in part, on a relative configuration of the third feature and the fourth feature in the image of the part of the sample at the first sample orientation and on a relative configuration of the third feature and the fourth feature in the image of the part of the sample at the second sample orientation.

7 . A microscopy system configured for acquiring tomographic images of a sample, wherein the microscopy system is configured to perform the method of claim 1 .

8 . The microscopy system of claim 7 , further comprising an imaging system configured to capture the image of the part of the sample, wherein the part of the sample comprises a feature, and wherein the microscopy system is configured to identify the feature in the image of the part of the sample, wherein the microscopy system comprises a data processing unit, wherein the data processing unit is configured to determine a configuration of the feature in the image of the part of the sample based on an artificial intelligence-based model.

9 . The microscopy system of claim 8 , wherein the artificial intelligence-based model comprises a supervised learning model.

10 . The microscopy system of claim 7 , further comprising an imaging system configured to capture the image of the part of the sample, wherein the part of the sample comprises a feature, and wherein the microscopy system is configured to identify the feature in the image of the part of the sample, wherein the microscopy system comprises a data processing unit, wherein the data processing unit is configured to determine the configuration of the feature in the image of the part of the sample using any of edge detection, filtering, feature detection, ridge detection, or any other image processing method.

11 . The method of claim 1 , wherein the microscopy system comprises the stage including the stage tilt axis and configured to position and/or orient the sample, and wherein the method comprises rotating the sample about the stage tilt axis to vary a tilt angle of the stage and change an orientation of the sample.

12 . The method of claim 11 , wherein the determination of the location in three-dimensional space of the defined region is based, at least in part, on the tilt angle of the stage.

13 . A computer program product comprising a non-transitory computer-readable medium storing instructions that, when run on a data processing unit of a microscopy system, perform a method of:

capturing an image of at least a part of a sample, the sample having a defined region including an exposure region having features that are of interest for imaging,

determining a location in three-dimensional space of the defined region of the sample by:

determining a first configuration, in a projection space, of a first feature of the sample in three-dimensional space relative to a configuration of a second feature of the sample in three-dimensional space,

determining a second configuration of a third feature in the part of the sample in three-dimensional space relative to a configuration of a fourth feature in the part of the sample in three-dimensional space,

comparing the relative configuration of the third feature and the fourth feature in the image of the part of sample to the relative configuration of the first feature and the second feature in the projection space to determine an angle between an axis of the sample and a tilt axis of a stage on which the sample is positioned, and

determining the location in three-dimensional space of the defined region based, at least in part, on the comparison of the relative configuration of the third feature and the fourth feature in the image of the part of the sample to the relative configuration of the first feature and the second feature in the projection space and the determination of the angle between the axis of the sample and the tilt axis of the stage; and

positioning a beam of particles over the exposure region based on the determined location in three-dimensional space of the exposure region.

14 . The computer program product of claim 13 , wherein the method further comprises generating a model of at least a modeled part of the sample, and wherein the determination of the location in three-dimensional space of the defined region is based, at least in part, on the model.

15 . The computer program product of claim 14 , wherein the method comprises

determining a projection of at least a projected part of the sample, wherein the projection is based, at least in part, on the model;

capturing an image of the projected part of the sample;

comparing the image and the projection of the projected part of the sample; and

refining the model based on the comparison between the image and the projection of the projected part of the sample.

16 . The computer program product of claim 14 , wherein the method comprises capturing images at a plurality of sample orientations, and wherein the image of the part of the sample comprises the image of the part of the sample at a first sample orientation.