Differential imaging with pattern recognition for process automation of cross sectioning applications
US-9881766-B2 · Jan 30, 2018 · US
US10811223B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10811223-B2 |
| Application number | US-201816155297-A |
| Country | US |
| Kind code | B2 |
| Filing date | Oct 9, 2018 |
| Priority date | Jun 9, 2015 |
| Publication date | Oct 20, 2020 |
| Grant date | Oct 20, 2020 |
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Producing and storing a first image, of a first, initial surface of the specimen; In a primary modification step, modifying said first surface, thereby yielding a second, modified surface; Producing and storing a second image, of said second surface; Using a mathematical Image Similarity Metric to perform pixel-wise comparison of said second and first images, so as to generate a primary figure of merit for said primary modification step.
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The invention claimed is: 1. A method comprising: acquiring, with a charged particle microscope, a first image of a first surface of a sample; performing a primary modification, with the charged particle microscope, of the first surface to produce a modified surface; acquiring, with the charged particle microscope, a second image of the modified surface; determining a level of similarity between the first and second images; comparing the level of similarity to a first threshold and a second, different, threshold; determining the primary modification failed to modify said first surface based on the level of similarity being above the first threshold, and performing a first modification of the modified surface; and determining modified surface is corrupted relative to the first surface due to the primary modification based on the level of similarity being below the second threshold, and performing a second modification of the modified surface, wherein the primary modification, the first modification and the second modification are different from each other. 2. The method of claim 1 , wherein determining a level of similarity between the first and second images comprises: performing a comparison of the first and second images using a mathematical image similarity metric to form a primary figure of merit, wherein the primary figure of merit quantifies the level of similarity of the first and second images. 3. The method of claim 2 , wherein the image similarity metric is selected from the group comprising SSIM, MSE, PSNR, MIR, and combinations and hybrids hereof. 4. The method of claim 2 , wherein performing the comparison of the first and second images includes performing a pixel-wise comparison. 5. The method of claim 1 , wherein the charged particle microscope includes one of the following for modifying the surface of the sample: a mechanical cutting tool; a Focused Particle Beam milling tool; an etching apparatus; a Beam-Induced Deposition tool; a PVD apparatus; a CVD apparatus, and combinations thereof. 6. The method of claim 1 , wherein the level of similarity is used to quantify a thickness change produced in the sample due to the primary modification step. 7. The method of claim 1 , wherein determining a level of similarity between the first and second images is performed without performing a scalarizing operation. 8. A charged-particle microscope comprising: a source to provide a beam of charged-particle radiation; an illuminator to direct the beam of charged-particle radiation to irradiate a surface of a sample; a detector to receive a flux of radiation emanating from the sample in response to the irradiation by the beam of charged-particle radiation, the detector coupled to produce an image of at least part of the surface; an apparatus to modify the surface of the sample, the apparatus coupled to modify the surface using a process chosen from the group comprising material removal, material deposition, and combinations thereof, wherein the modification is based on a first set of operating parameters of the apparatus; and a processor, coupled at least to the detector and apparatus, including code that, when executed by the processor, causes the charged-particle microscope to: acquire a first image of a first surface of the sample; modify, in a primary modification step, with the apparatus operating in response to a first set of operating parameters, the first surface to produce a modified surface; acquire a second image of the modified surface; determine a level of similarity between the first and second images; compare the level of similarity to first and second thresholds; and determining the primary modification failed to modify said first surface based on the level of similarity being above the first threshold, perform a first modification of the modified surface, wherein the performance of the first modification of the modified surface is based on a second set of operating parameters, the second operating parameters different from the first set of operating parameters, and determining the modified surface is corrupted relative to the first surface due to the primary modification based on the level of similarity being below the second threshold, perform a second modification of the modified surface, the second modification different than the first modification. 9. The charged-particle microscope of claim 8 , wherein the code that causes the charged-particle microscope to determine a level of similarity between the first and second images comprises, further includes code that, when executed by the processor, causes the charged-particle microscope to: perform a comparison of the first and second images using a mathematical image similarity metric to form a primary figure of merit, wherein the primary figure of merit quantifies the level of similarity of the first and second images. 10. The charged-particle microscope of claim 9 , wherein the image similarity metric is selected from the group comprising SSIM, MSE, PSNR, MIR, and combinations and hybrids hereof. 11. The charged-particle microscope of claim 9 , wherein performing the comparison of the first and second images includes performing a pixel-wise comparison. 12. The charged particle microscope of claim 8 , wherein the first set of parameters includes at least a parameter influences the thickness of material removed from or added to a surface by the primary modification step. 13. The charged particle microscope of claim 8 , wherein the performance of the second modification of the modified surface is based on a third set of operating parameters, the third set of operating parameters different from the second set of operating parameters. 14. The charged-particle microscope of claim 8 , wherein the apparatus is selected from the group comprising: a mechanical cutting tool; a Focused Particle Beam milling tool; an etching apparatus; a Beam-Induced Deposition tool; a PVD apparatus; a CVD apparatus, and combinations thereof. 15. The charged-particle microscope of claim 14 , wherein the operating parameters at least include one or more of: cutting tool position, focused particle beam position, assistive gas pressure, duration of process, and combinations thereof. 16. The charged-particle microscope of claim 8 , wherein the level of similarity is used to quantify a thickness change produced in the sample due to the modification step. 17. The charged-particle microscope of claim 8 , wherein the determination of a level of similarity between the first and second images is performed without performing a scalarizing operation.
Detectors; Associated components or circuits therefor · CPC title
Surface alteration · CPC title
Controlling tubes by information coming from the objects {or from the beam}, e.g. correction signals · CPC title
Image processing · CPC title
Electron or ion microscopes; Electron or ion diffraction tubes · CPC title
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