DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/08/2024 was filed in compliance with the provisions of 37 CFR 1.97 and 1.98. Accordingly, the information disclosure statement is being considered by the examiner.
Applicant has not provided an explanation of relevance of cited document(s) discussed below.
Reference US 2019/0355544 A1 is a general background reference covering: A charged particle beam system includes a charged particle source, a multi beam generator, an objective lens, a projection system, and a detector system. The projection system includes a first subcomponent configured to provide low frequency adjustments, and the projection system comprises a second subcomponent configured to provide a high frequency adjustments. (see abstract).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-21, 26, 27 are rejected under 35 U.S.C. 103 as being unpatentable over Wieland et al. (Wieland) (WO 2022242984 A1).
Regarding claim 1, Wieland discloses a method (e.g., there is provided a computer implementable method of computer readable instructions that when read by a computer to cause the computer to perform the method of detecting defects in sample images, paragraph 7), comprising:
providing a reference image of the sample (e.g., providing a reference image based on at least one source image, paragraph 7);
dividing the sample image into sample image regions (e.g., applying a uniform filter comprises convoluting the sample image with a uniform kernel. The size of the uniform kernel is determined, e.g. by the user, for inspection of a given sample based on, for example, the size of features on the sample, paragraph 98);
dividing the reference image into reference image regions, each sample image region being assigned a reference image region to form an image region pair (e.g., More desirably, the result of the comparison is a difference value representing the magnitude of the difference between the sample image and the reference image. Desirably, the result of the comparison is a difference value for each pixel (or each group of adjacent pixels which may be referred to a ‘region of pixels’), paragraph 91);
for each image region pair, identifying a structure that is present both in the sample image region and the reference image region (e.g., In cases where the sample image is compared to a reference image derived from live source images, the roles of the different images may rotate. For example if three images A B and C are output by a charged particle assessment device: A and B may be averaged to provide a reference image to compare to C; A and C may be averaged to provide a reference image to compare to B; while B and C are averaged to provide a reference image to compare to A, paragraph 90);
registering the sample image regions by correcting a lateral offset of the identified structure in each sample image region based on the location of the identified structure in the respectively assigned reference image region, thereby forming corrected sample image regions (e.g., receiving a sample image from the charged particle beam system; applying a filter to the sample image to generate a filtered sample image, applying the filter comprising performing a convolution between the sample image and a kernel; providing a reference image based on at least one source image; and comparing the filtered sample image to the reference image so as to detect defects in the sample image, paragraph 7).
Wieland, in one embodiment does not specifically disclose providing a sample image which is rotated relative to the reference image, the sample image having been generated using a particle beam inspection system;
comparing each corrected sample image region pixel by pixel with the respectively associated reference image region to perform defect detection of the sample.
Wieland, in second embodiment discloses providing a sample image which is rotated relative to the reference image, the sample image having been generated using a particle beam inspection system (e.g., a filter module configured to apply a filter to the sample image to perform a convolution between the sample image and a kernel and to generate a filtered sample image; a reference image module configured to provide a reference image based on one or more source images, paragraph 8);
comparing each corrected sample image region pixel by pixel with the respectively associated reference image region to perform defect detection of the sample (e.g., a filter module configured to apply a filter to the sample image to perform a convolution between the sample image and a kernel and to generate a filtered sample image; a reference image module configured to provide a reference image based on one or more source images; and a comparator configured to compare the filtered sample image to the reference image so as to detect defects in the sample image, paragraph 8).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to have modified Wieland in one embodiment to include disclose providing a sample image which is rotated relative to the reference image, the sample image having been generated using a particle beam inspection system; comparing each corrected sample image region pixel by pixel with the respectively associated reference image region to perform defect detection of the sample as taught by Wieland in second embodiment It would have been obvious to one of ordinary skill in the art at the time of the invention to have modified Wieland in first embodiment by the teaching of Wieland in second embodiment to detect defects in the sample image.
Regarding claim 2, Wieland discloses wherein, for each of at least some of the sample image regions, an edge length of the sample image region is at least five times a size of a maximum distortion in the sample image region (e.g., the efficiency and effectiveness of noise reduction in the sample image may be optimized by suitable selection of the size of the uniform filter. The optimum size of the filter may depend on factors such as the resolution of the sample images and the size of features on the sample being inspected, paragraph 87).
Regarding claim 3, Wieland discloses further comprising:
providing an expected defect size (e.g., When selecting pixels for further processing as candidate or actual defects, it is desirable to select a region around the pixel, or a region of pixels, that has been identified as differing from the reference image, paragraph 94); and
defining an edge length of the sample image region such that a location- dependent distortion does not change more significantly over a sample image region than half the expected defect size (e.g., The region may be referred to as a clip and is desirably of sufficient size to allow further automated or manual inspection to determine whether or not a significant defect is present. The above-described data processing method may be used with either single-column or multi- column assessment systems, paragraphs 94, 95), wherein grad is an absolute value of the gradient of the location-dependent distortion (e.g., paragraph 91)
Regarding claim 4, Wieland discloses wherein a respective lateral offset of the respectively identified structure is corrected in two directions which are linearly independent of each other (e.g., The reconstructed images can be used to reveal various features of the internal or external structures of the sample 208. The reconstructed images can thereby be used to reveal any defects that may exist in the sample, paragraph 44).
Regarding claim 5, Wieland discloses wherein a size of the sample image regions is selected, when dividing the sample image, such that a shape of the sample image regions does not substantially change due to the distortion (e.g., For high throughput inspection, some of the inspection apparatuses use multiple focused beams, i.e. a multi-beam, of primary electrons. The component beams of the multi-beam may be referred to as sub-beams or beamlets. A multi-beam can scan different parts of a sample simultaneously. A multi-beam inspection apparatus can therefore inspect a sample at a much higher speed than a single -beam inspection apparatus, paragraph 30).
Regarding claim 6, Wieland discloses wherein:
the sample image regions are quadrangular (e.g., FIG. 11 is, by way of an example, an image, or even part of an image and thus a clip, of a sample generated by a charged particle assessment device, paragraph 103); and
distances between corners of the sample image regions are shifted relative to one another with respect to associated distances between the corners of the reference image regions relative to one another due to the distortion by no more than a predetermined number of pixels (e.g., It will be seen that the sample inspected has a repeating pattern of features with a unit cell of size indicted by the dimensions ShiftX and ShiftY, paragraph 103, figure 11).
Regarding claim 7, Wieland discloses wherein the distances between the corners of the sample image regions are shifted relative to one another with respect to the associated distances between the corners of the reference image regions relative to one another due to the distortion by no more than half an expected defect size (e.g., Each version of the source image is shifted by integer multiples of ShiftX and/or ShiftY. If either or both dimensions of the unit cell are not equal to an integer number of pixels, the shift amount can be rounded to the nearest pixel or a fractional pixel shift can be effected by linear interpolation. Another possibility is to shift by a multiple of the pitch of the repeating pattern such that the multiple is an integer number of pixels. In effect, multiple instances of the unit cell are extracted from the source image and averaged. This approach may be referred to as an example of array mode. The same reference image may be used for comparison with different instances of a sample image such as in array mode, paragraph 106).
Regarding claim 8, Wieland discloses wherein mutually adjacent sample image regions have an overlap, and the overlap is as large as a size of an expected defect (e.g., The electron distribution data, collected during a detection time window, can be used in combination with corresponding scan path data of each of primary sub-beams 211, 212, and 213 incident on the sample surface, to reconstruct images of the sample structures under inspection. The reconstructed images can be used to reveal various features of the internal or external structures of the sample 208. The reconstructed images can thereby be used to reveal any defects that may exist in the sample, paragraph 44).
Regarding claim 9, Wieland discloses wherein the sample image has, with respect to the reference image: an affine distortion in addition to the rotation; and/or a non-linear distortion (e.g., Detection of defects may be done by comparing an image of a part of the sample, referred to herein as a sample image, to a reference image. Any pixel that differs from the corresponding pixel of the reference image may be considered a defect, with adjacent pixels that differ from the reference image being considered a single defect. However, an overly-strict approach to labeling pixels as defective may result in false positives, i.e. samples being labelled as having defects when in fact no significant defect is present. False positives are likely in the case where either or both the sample image or the reference image has noise. Therefore, it is desirable to apply noise reduction to either or both the reference image and the sample image, paragraph 86).
Regarding claim 10, Wieland discloses further comprising determining a distortion function or a distortion pattern f Regarding claim 1, Wieland discloses or the sample image based on the corrected lateral offset of the sample image regions during registration (e.g., provided a data processing device for detecting defects in sample images generated by a charged particle assessment system, the device comprising: an input module configured to receive a sample image from the charged particle assessment system; a filter module configured to apply a filter to the sample image to perform a convolution between the sample image and a kernel and to generate a filtered sample image, paragraph 8).
Regarding claim 11, Wieland discloses further comprising determining rotation angle of the sample image with respect to the reference image (e.g., n cases where the sample image is compared to a reference image derived from live source images, the roles of the different images may rotate. For example if three images A B and C are output by a charged particle assessment device: A and B may be averaged to provide a reference image to compare to C; A and C may be averaged to provide a reference image to compare to B; while B and C are averaged to provide a reference image to compare to A, paragraph 90).
Regarding claim 12, Wieland discloses further comprising adjusting and/or calibrating the particle beam inspection system based on the distortion function and/or the distortion pattern (e.g., Pattern inspection apparatuses with a charged particle beam have been used to inspect objects, which may be referred to as samples, for example to detect pattern defects, paragraph 4).
Regarding claim 13, Wieland discloses further comprising coarsely registering the sample image with respect to the reference image (e.g., receiving a sample image from the charged particle beam system; applying a filter to the sample image to generate a filtered sample image, applying the filter comprising performing a convolution between the sample image and a kernel; providing a reference image based on at least one source image, paragraph 7).
Regarding claim 14, Wieland discloses wherein the particle beam inspection system comprises an individual particle beam system (e.g., a computer implementable method of computer readable instructions that when read by a computer to cause the computer to perform the method of detecting defects in sample images generated by a charged particle beam system, paragraph 7).
Regarding claim 15, Wieland discloses wherein the particle beam inspection system comprises a multiple particle beam system (e.g., the method of detecting defects in sample images generated by a charged particle beam system, paragraph 7).
Regarding claim 16, Wieland discloses comprising performing the method for a plurality of sample images, wherein each sample image is generated using an individual particle beam assigned thereto (e.g., the method of detecting defects in sample images generated by a charged particle beam system, paragraph 7).
Regarding claim 17, Wieland discloses wherein the multiple particle beam system comprises a single column for the plurality of individual particle beams (e.g., FIG. 2, which is a schematic diagram illustrating an exemplary electron beam system 40, including a multi-beam electron-optical system 41, that is part of the exemplary charged particle beam inspection system 100 of FIG. 1. The electron beam system 40 comprises an electron source 201 and a projection apparatus 230. The electron beam system 40 further comprises a motorized stage 209 and a sample holder 207. The electron source 201 and projection apparatus 230 may together be referred to as the electron-optical system 41 or as an electron-optical column, paragraph 37).
Regarding claim 18, Wieland discloses comprising performing the method for the plurality of sample images in a shell-wise manner (e.g., the electron beam system 40 further comprises a motorized stage 209 and a sample holder 207. The electron source 201 and projection apparatus 230 may together be referred to as the electron-optical system 41 or as an electron-optical column. The sample holder 207 is supported by motorized stage 209 so as to hold a sample 208 (e.g., a substrate or a mask) for inspection, paragraph 37).
Regarding claim 19, Wieland discloses wherein:
the sample images are arranged hexagonally with respect to one another; and/or wherein the sample images have an overlap with adjacent sample images (e.g., each surrounding a beam aperture 406. The beam apertures 406 may be formed by etching through the substrate 404. In the arrangement shown in FIG. 7, the beam apertures 406 are in a hexagonal close packed array. The beam apertures 406 can also be differently arranged, e.g. in a rectangular, or a rhombic, array. The beam arrangement of the hexagonal arrangement in FIG. 7 may be more densely packed than a square beam arrangement. The detector elements 405 may be arranged in a rectangular array or a hexagonal array, paragraph 74).
Regarding claim 20, Wieland discloses further comprising:
selecting a sample image as base sample image (e.g., the method comprising: receiving a sample image from the charged particle beam system, paragraph 7). The remaining of limitations are rejected as set forth above as claim 1.
Regarding claim 21, Wieland discloses further comprising determining a first angle of rotation for the distortion based on the sample image region-wise registration of the first sample images of the first shell (e.g., Each of the plate electrode arrays may be referred to as a control electrode. A function of control lens array 250 is to optimize the beam opening angle with respect to the demagnification of the beam and/or to control the beam energy delivered to the objective lenses 234, each of which directs a respective sub-beam 211, 212, 213 onto the sample 208, paragraph 52).
Regarding claim 26, Wieland discloses one or more machine-readable hardware storage devices comprising instructions that are executable by one or more processing devices (e.g., The signal processing system 280 may include an image acquirer (not shown) and a storage device (not shown). For example, the signal processing system may comprise a processor, computer, server, mainframe host, terminals, personal computer, any kind of mobile computing devices, and the like, or a combination thereof, paragraph 43) to perform operations comprising the method of claim 1. The remaining limitations is rejected as set forth above as claim 1.
Regarding claim 27, Wieland discloses a system, comprising:
one or more processing devices; and
one or more machine-readable hardware storage devices comprising instructions that are executable by one or more processing devices (e.g., the controller 50 is electronically connected to electron beam system 40. The controller 50 may be a processor (such as a computer) configured to control the charged particle beam inspection apparatus 100. The controller 50 may also include a processing circuitry configured to execute various signal and image processing functions. While the controller 50 is shown in FIG. 1, paragraph 36) to perform operations comprising the method of claim 1. The remaining limitations is rejected as set forth above as claim 1.
Allowable Subject Matter
Claim 22 is allowed.
Claim 22 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Referring to claim 22, the prior art searched and of record neither anticipates nor suggests in the claimed combinations, [22. The method of claim 21, further comprising:
selecting second sample images that are arranged in a second shell around the base sample image; correcting a position of the second sample images based on the determined first angle of rotation; and performing a) to g) for the position-corrected second sample images.].
Claims 23 - 25 are dependent on claim 22.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to QUANG N VO whose telephone number is (571)270-1121. The examiner can normally be reached Monday-Friday, 7AM-4PM, EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mohammad K Ghayour can be reached at 571-272-3021. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/QUANG N VO/Primary Examiner, Art Unit 2683