Segmentation-based care area setting for specimen inspection using edge detection

Abstract

A method and system for establishing a care area (CA) for the inspection of a specimen are provided. One system includes a computer subsystem configured to acquire a region of interest image for a specimen from an image of a specimen generated by an imaging subsystem. The computer subsystem separates the image into pixels corresponding to one or more specimen structures within the image, which have different intensities from other pixels within the image, by segmenting the region of interest image based on the intensity of pixels within the image. Additionally, the computer subsystem detects edges of specimen structures within the image based on pixels corresponding to specimen structures, and determines the characteristic(s) of one or more CAs within the image of the specimen based on the detected edges. The computer subsystem also stores information about the CA(s) for use in the inspection of the specimen.

Description

Technology Field

[0001] Field of invention

[0002] The present invention generally relates to a system and method for establishing a care area for the inspection of a specimen. A specific embodiment relates to using image intensity and edge detection to establish a care area. Background Technology

[0003] Description of related technology

[0004] The following descriptions and examples are not recognized as prior art on the grounds that they are included in this section.

[0005] Inspection processes are used at various stages of the semiconductor manufacturing process to detect defects on reticles and wafers, thereby promoting higher yields and consequently higher profits. Inspection has always been a critical part of semiconductor device fabrication. However, as the dimensions of semiconductor devices decrease, inspection becomes even more critical for the successful manufacturing of acceptable semiconductor devices, as smaller defects can cause the device to fail.

[0006] A "care area," as commonly referred to in the relevant technical field, is an area on a specimen of interest for inspection purposes. Sometimes, a care area (CA) is used in an inspection process to distinguish an area on the specimen that is being inspected from an area on the specimen that is not being inspected. Additionally, a CA is sometimes used to distinguish areas on the specimen to be inspected by one or more different parameters. For example, if a first area of ​​the specimen is more critical than a second area, the first area may be inspected with higher sensitivity than the second area so that defects are detected with higher sensitivity in the first area. Other parameters of the inspection process may be changed for each CA in a similar manner.

[0007] Different categories of inspection CAs are currently in use. One category is legacy CAs, which are traditionally drawn manually. As almost all users adopt design-guided inspection, legacy CAs are rarely used now. Another category is design-based CAs. These are CAs derived based on heuristics regarding the chip design patterns printed on the specimen. Users attempt to review the chip design and derive methods / scripts to assist in deriving CAs. Numerous techniques and tools exist to define these design-based CAs. Because they are derived from ground truth (chip design), they can provide high precision and substantially small CAs, and also allow inspection systems to store large volumes of CAs. These CAs are not only important from the perspective of defect detection, but they are also often critical for noise suppression.

[0008] Although multiple methods exist for generating CA, the inventors do not recognize any method that uses pixel intensity from die-based features to generate CA. Intensity-based segmentation can currently be used to flag pixels to adjust sensitivity (e.g., setting defect detection algorithms). However, this does not provide the flexibility offered by CA. In other words, setting defect detection thresholds based on the intensity of different pixel segments can help suppress nuisance and noise within the inspection results while attempting to detect defects with the required sensitivity, but it does not offer as many options as CA provides, such as intentionally inspecting specific regions or structures on a specimen with specified defect detection parameters.

[0009] Many currently used CA setup methods and systems also have numerous drawbacks. For example, methods for setting up CA using design information about a specimen are computationally expensive and require access to intellectual property such as graphical data stream (GDS) files. However, the entity that owns and / or operates the inspection tool may not be the same as the entity that owns the design fabricated on the specimen being inspected by the tool. Consequently, design information about the specimen may not be available at all in some inspection tool use cases. Furthermore, manually drawing CA has obvious disadvantages. For instance, while CA can be drawn manually to isolate target features, this is clearly time-consuming and labor-intensive, as there may be over 1,000 intricate features within a die. Therefore, in many cases, manual CA setup is very costly and impractical, so it is relied upon only when other automation or semi-automation options are unavailable.

[0010] Therefore, it would be advantageous to develop a system and method for establishing CA for specimen inspection that does not have one or more of the disadvantages described above.

[0011] The following description of various embodiments is not to be interpreted as limiting the subject matter of the appended claims in any way.

[0012] One embodiment relates to a system configured to establish a care area (CA) for the inspection of a specimen. The system includes an imaging subsystem configured to generate an image of the specimen and a computer subsystem configured to acquire a region of interest image of the specimen from one or more of the images generated by the imaging subsystem. The computer subsystem is also configured to separate the region of interest image into pixels corresponding to one or more specimen structures within the region of interest image having an intensity different from other pixels within the region of interest image by segmenting the region of interest image based on the intensity of pixels within the region of interest image. Additionally, the computer subsystem is configured to detect edges of one or more specimen structures within the region of interest image based on pixels corresponding to one or more specimen structures and to determine one or more characteristics of one or more CAs within the image of the specimen based on the detected edges. The computer subsystem is also configured to store information about one or more CAs for use in the inspection of the specimen. The system may also be configured as described herein.

[0013] Another embodiment relates to a computer-implemented method for establishing a CA for the inspection of a specimen. The method includes the steps of acquiring, segmenting, detecting, determining, and storing as described above. The steps of the method are performed by a computer subsystem coupled to the imaging subsystem described above. Each step of the method may be performed as further described herein. The method may include any other step(s) of any other method(s) described herein. The method may be performed by any of the systems described herein.

[0014] Another embodiment relates to a non-transient computer-readable medium storing program instructions executable on a computer system for performing a computer-implemented method for establishing a CA for testing a specimen. The computer-implemented method includes steps of the method described above. The computer-readable medium may also be configured as described herein. Steps of the computer-implemented method may be performed as further described herein. Additionally, the computer-implemented method in which program instructions are executable may include any other step(s) of any other method(s) described herein. Brief explanation of the drawing

[0015] Further advantages of the present invention will become apparent to those skilled in the art with the help of the following detailed description of preferred embodiments and with reference to the accompanying drawings, wherein: FIGS. 1 and 2 are schematic diagrams illustrating a side view of an embodiment of a system configured as described in this specification; FIG. 3 is a flowchart illustrating an example of a step performed by a computer subsystem described herein to establish a care area for the inspection of a specimen; FIGS. 4 and 5 are plan views of examples of specimen structures within a design and schematic diagrams illustrating embodiments of specimen structures within an image generated by an imaging subsystem, acquired images, segmentation results, binary images, and care areas generated by embodiments described herein; FIG. 6 is a schematic diagram illustrating a plan view of an example of a specimen structure in an image obtained according to an embodiment described herein and an example of a plot generated for a different embodiment of the division described herein; and FIG. 7 is a block diagram illustrating an embodiment of a non-transient computer-readable medium that stores program instructions for a computer system to perform a computer implementation method described in this specification. Although the invention may be made in various modifications and alternative forms, specific embodiments thereof are illustrated by way of example in the drawings and described in detail herein. The drawings may not be in scale. However, it should be understood that the drawings and the detailed description thereof are not intended to limit the invention to the specific form disclosed, but on the contrary, are intended to cover all modifications, equivalents, and alternatives that fall within the spirit and scope of the invention as defined by the appended claims. Specific details for implementing the invention

[0016] As used herein, the term “defect of interest (DOI)” is defined as a defect detected on a specimen that is actually a defect on the specimen. Therefore, since users are generally interested in how many actual defects exist on a specimen being inspected and what types of actual defects exist, the DOI is of interest to the user. In some contexts, the term “DOI” is used to refer to a subset of all actual defects on a specimen, and the subset includes only the actual defects of interest to the user. For example, multiple types of DOIs may exist on any given specimen, and one or more of them may be of greater interest to the user than one or more other types. However, in the context of the embodiments described herein, the term “DOI” is used to refer to any and all actual defects on a specimen.

[0017] The term "nusense" (which is sometimes used interchangeably with "nusense defect") as used herein is defined as an event that is detected on a specimen and / or is not actually a defect on the specimen, but is generally of no interest to the user. Nusenses that are not actually defects may be detected as events due to non-defective noise sources on the specimen (e.g., grain within metal lines on the specimen, signals from underlying layers or materials on the specimen, line edge roughness (LER), relatively small critical dimension (CD) variations of patterned properties, thickness variations, etc.) and / or due to the marginality of the inspection system itself or its configuration used for inspection.

[0018] The terms “design,” “design data,” and “design information,” as used interchangeably herein, generally refer to the physical design (layout) of an IC or other semiconductor device and data derived from the physical design through complex simulation or simple geometric and Boolean operations. The design may include any other design data or design data proxies described in the jointly owned U.S. Patent No. 7,570,796, registered to Zafar et al. on August 4, 2009, and U.S. Patent No. 7,676,077, registered to Kulkarni et al. on March 9, 2010, all of which are incorporated by reference as fully described herein. Additionally, the design data may be standard cell library data, integrated layout data, design data for one or more layers, derivatives of the design data, and whole or part chip design data. Additionally, the “design,” “design data,” and “design information” described in this specification refer to data and information generated by a semiconductor device designer during the design process and are therefore available for use long prior to printing of the design on any physical specimen, such as a reticle and a wafer.

[0019] Returning to the drawings, it should be noted that they are not drawn to scale. In particular, the scale of some of the elements in the drawings is greatly exaggerated to emphasize the characteristics of the elements. Additionally, it should be noted that the drawings are not drawn to the same scale. Elements that may be illustrated in more than one drawing and configured similarly are indicated using the same reference number. Unless otherwise stated in this specification, any of the elements described and illustrated may include any suitable commercially available element.

[0020] One embodiment relates to a system configured to establish a care area (CA) for the inspection of a specimen. A specific embodiment described herein is configured for a segment-based CA setting for patterned wafer inspection using an edge detection algorithm or method. For example, an embodiment described herein provides a CA setting guided by specimen structures (e.g., die features) within a specimen image and differences in their intensity.

[0021] The embodiments described in the specification have numerous advantages, such as providing improved inspection sensitivity by generating intensity-based CA for specimen structure-based features. The embodiments also provide a method for segmenting specimen structure-based features (which are mostly brighter than the background and are typically a source of noise in light scattering-based tools) by marking corresponding pixels based on their differential scattering intensity (i.e., the difference in intensity between pixels within an image). Additionally, the embodiments advantageously use edge detection to mark corresponding polygons and record their coordinates. The recorded coordinates can be used to generate CA. The embodiments are independent of the inspection platform and can be applied to any patterned wafer regardless of process layer, type, or technology.

[0022] In one embodiment, the specimen is a wafer. The wafer may include any wafer known in the field of semiconductor technology. While some embodiments may be described herein with respect to wafers or wafers, the embodiments are not limited to specimens in which they may be used. For example, the embodiments described herein may be used in specimens such as reticles, flat panels, personal computer (PC) boards, and other semiconductor specimens.

[0023] In this specification, the term “specimen structure” is used interchangeably with the terms “die feature,” “patterned feature,” and “specimen feature.” Generally, the term “specimen structure” is defined in this specification as a feature within the design of a specimen that is formed on the specimen during the fabrication process. The term “specimen structure” is also used in this specification to refer to a design feature that is patterned on the specimen, in contrast to an unpatterned layer included in some designs. Accordingly, the “specimen structure” described in this specification is generally formed on the specimen as described in this specification during processes such as lithography and / or etching. Additionally, while some defects or foreign substances (such as particles, fall-on material, and residual material) may be considered as structures on the specimen in some cases, they are not considered as specimen structures in the embodiments described in this specification. Instead, the term “specimen structure” as used in this specification refers only to structures intentionally formed on the specimen during one or more stages of the fabrication process.

[0024] One embodiment of such a system includes an imaging subsystem configured to generate an image of a specimen. Generally, the imaging subsystem includes at least an energy source and a detector. The energy source is configured to generate energy directed toward the specimen. The detector is configured to detect energy from the specimen and generate an output that responds to the detected energy.

[0025] In one embodiment, the imaging subsystem is a light-based imaging subsystem. For example, in an embodiment of the system illustrated in FIG. 1, the imaging subsystem (10) includes an illumination subsystem configured to direct light toward a specimen (14). The illumination subsystem includes at least one light source, such as a light source (16). The illumination subsystem is configured to direct light toward the specimen at one or more angles of incidence, and the one or more angles of incidence may include one or more oblique angles and / or one or more normal angles. As illustrated in FIG. 1, light from the light source (16) is directed through an optical element (18) and then through a lens (20) to a beam splitter (21), which directs the light toward the specimen (14) at a normal angle of incidence. The angles of incidence may include any suitable angles of incidence, and the angles of incidence may vary, for example, depending on the characteristics of the specimen and the defects to be detected on the specimen.

[0026] The illumination subsystem may be configured to direct light toward a specimen at different angles of incidence at different times. For example, the imaging subsystem may be configured to modify one or more characteristics of one or more elements of the illumination subsystem so that light may be directed toward the specimen at an angle of incidence different from the angle of incidence shown in FIG. 1. In one such example, the imaging subsystem may be configured to move the light source (16), optical element (18), and lens (20) so that light may be directed toward the specimen at different angles of incidence.

[0027] In some cases, the imaging subsystem may be configured to direct light toward a specimen at more than one angle of incidence simultaneously. For example, the imaging subsystem may include more than one illumination channel, and one of the illumination channels may include a light source (16), an optical element (18), and a lens (20) as illustrated in FIG. 1, and another of the illumination channels (not illustrated) may include a similar element, which may be configured differently or identically, or at least may include a light source and may include one or more other components as further described herein. When such light is directed toward a specimen simultaneously with other light, one or more characteristics (e.g., wavelength, polarization, etc.) of the light directed toward the specimen at different angles of incidence may be different, and accordingly, the light generated from the illumination of the specimen at different angles of incidence may be distinguished from one another at the detector(s).

[0028] In another example, the lighting subsystem may include only one light source (e.g., the light source (16) shown in FIG. 1), and light from the light source may be separated into different optical paths (e.g., based on wavelength, polarization, etc.) by one or more optical elements (not shown) of the lighting subsystem. Then, light in each of the different optical paths may be directed toward a specimen. Multiple lighting channels may be configured to direct light toward the specimen simultaneously or at different times (e.g., when different lighting channels are used to sequentially illuminate the specimen). In another example, the same lighting channel may be configured to direct light having different characteristics toward the specimen at different times. For example, in some cases, the optical element (18) may be configured as a spectral filter, and the characteristics of the spectral filter may be changed in various different ways (e.g., by replacing the spectral filter), so that light of different wavelengths may be directed toward the specimen at different times. The illumination subsystem may have any other suitable configuration known in the art for directing light having different or identical characteristics onto a specimen sequentially or simultaneously at different or identical angles of incidence.

[0029] In one embodiment, the light source (16) includes a broadband plasma (BBP) light source. In this way, the light generated by the light source and directed toward the specimen may include broadband light. However, the light source may include any other suitable light source, such as a laser, and the laser may be any suitable laser known in the art configured to generate light at any suitable wavelength(s) known in the art. The laser may be configured to generate monochromatic or nearly monochromatic light. In this way, the laser may be a narrowband laser. The light source may also include a polychromatic light source that generates light at a number of individual wavelengths or wavelength bands.

[0030] Light from the optical element (18) can be focused into a beam splitter (21) by a lens (20). Although the lens (20) is shown as a single refractive optical element in FIG. 1, in practice, the lens (20) may include a plurality of refractive and / or reflective optical elements combined to focus light from the optical element onto a specimen. The illumination subsystem shown in FIG. 1 and described herein may include any other suitable optical elements (not shown). Examples of such optical elements include, but are not limited to, polarizing components(s), spectral filters(s), spatial filters(s), reflective optical elements(s), apodizer(s), beam splitter(s), aperture(s), and similar elements, which may include any such suitable optical elements known in the art. Additionally, the system may be configured to change one or more elements of the illumination subsystem based on the type of illumination to be used for imaging.

[0031] The imaging subsystem may also include a scanning subsystem configured to allow light to be scanned across the specimen. For example, the imaging subsystem may include a stage (22) on which the specimen (14) is placed during imaging. The scanning subsystem may include any suitable mechanical and / or robotic assembly (including the stage (22)) that may be configured to move the specimen so that light can be scanned across the specimen. Additionally, or alternatively, the imaging subsystem may be configured such that one or more optical elements of the imaging subsystem perform partial scanning of light across the specimen. The light may be scanned across the specimen in any suitable manner.

[0032] The imaging subsystem further includes one or more detection channels. At least one of the one or more detection channels includes a detector configured to detect light from a specimen due to illumination of the specimen by the imaging subsystem and to generate an output in response to the detected light. For example, the imaging subsystem illustrated in FIG. 1 includes two detection channels: one detection channel formed by a collector (24), an element (26), and a detector (28), and another detection channel formed by a collector (30), an element (32), and a detector (34). As illustrated in FIG. 1, the two detection channels are configured to collect and detect light at different collection angles. In some cases, one detection channel is configured to detect specularly reflected light, and the other detection channel is configured to detect light that is not specularly reflected from the specimen (e.g., scattered, diffracted, etc.). However, two or more of the detection channels may be configured to detect the same type of light (e.g., specularly reflected light) from the specimen. FIG. 1 illustrates an embodiment of an imaging subsystem comprising two detection channels, but the imaging subsystem may comprise a different number of detection channels (e.g., a single detection channel or two or more detection channels). Each collector is illustrated as a single refractive optical element in FIG. 1, but each collector may comprise one or more refractive optical element(s) and / or one or more reflective optical element(s).

[0033] One or more detection channels may include any suitable detector known in the art, such as a photo-multiplier tube (PMT), a charge-coupled device (CCD), and a time-delay integration (TDI) camera. The detector may also include a non-imaging detector or an imaging detector. If the detector is a non-imaging detector, each detector may be configured to detect specific characteristics of scattered light, such as intensity, but may not be configured to detect these characteristics as a function of position within the imaging plane. As such, the output generated by each detector included in each detection channel may be a signal or data, but may not be an image signal or image data. In this case, a computer subsystem, such as the computer subsystem (36), may be configured to generate an image of the specimen from the non-imaging output of the detector. However, in other cases, the detector may be configured as an imaging detector configured to generate an imaging signal or image data. Thus, the imaging subsystem may be configured to generate an image in a number of ways.

[0034] The computer subsystem (36) of the system may be coupled to the detector of the imaging subsystem in any suitable manner (e.g., via one or more transmission media including "wired" and / or "wireless" transmission media) so that the computer subsystem can receive the output generated by the detector during the scanning of the specimen. The computer subsystem (36) may be configured to perform a number of functions and any other functions further described herein using the output of the detector as described herein. This computer subsystem may also be configured as described herein.

[0035] These computer subsystems (as well as other computer subsystems described herein) may also be referred to as computer system(s) in this specification. Each of the computer subsystem(s) or system(s) described herein may take various forms, including personal computer systems, image computers, mainframe computer systems, workstations, network appliances, internet appliances, or other devices. Generally, the term “computer system” may be broadly defined to encompass any device having one or more processors that execute instructions from a memory medium. Computer subsystem(s) or system(s) may also include any suitable processor known in the art, such as a parallel processor. Additionally, computer subsystem(s) or system(s) may include a computer platform having high-speed processing and software, as a standalone tool or a network tool.

[0036] If the system includes more than one computer subsystem, different computer subsystems may be combined with each other so that images, data, information, instructions, etc. can be transmitted between computer subsystems as further described herein. For example, a computer subsystem (36) may be combined to computer subsystem(s) (102) (as illustrated by the dashed line in FIG. 1) by any suitable transmission medium that may include any suitable wired and / or wireless transmission medium known in the art. Two or more of these computer subsystems may also be effectively combined by a shared computer-readable storage medium (not shown).

[0037] Although the imaging subsystem is described above as an optical or light-based subsystem, the imaging subsystem may be an electronic-based subsystem. For example, in one embodiment, the energy directed toward the specimen contains electrons, and the energy detected from the specimen contains electrons. In this way, the energy source may be an electron beam source. In this embodiment illustrated in FIG. 2, the imaging subsystem includes an electron column (122) coupled to a computer subsystem (124).

[0038] As also illustrated in FIG. 2, the electron column comprises an electron beam source (126) configured to generate electrons focused onto a specimen (128) by one or more elements (130). The electron beam source may include, for example, a cathode source or an emitter tip, and one or more elements (130) may include, for example, a gun lens, an anode, a beam limiting aperture, a gate valve, a beam current selecting aperture, an objective lens, and a scanning subsystem, all of which may include any such suitable elements known in the art.

[0039] Electrons returned from the sample (e.g., secondary electrons) can be focused to a detector (134) by one or more elements (132). One or more elements (132) may include a scanning subsystem, for example, which may be the same scanning subsystem included in the element(s) (130).

[0040] The electronic column may include any other suitable elements known in the art. Additionally, the electronic column may be further configured as described in U.S. Patent No. 8,664,594, registered to Jiang et al. on April 4, 2014; U.S. Patent No. 8,692,204, registered to Kojima et al. on April 8, 2014; U.S. Patent No. 8,698,093, registered to Gubbens et al. on April 15, 2014; and U.S. Patent No. 8,716,662, registered to MacDonald et al. on May 6, 2014, which are incorporated by reference as fully presented herein.

[0041] Although the electron column is illustrated in FIG. 2 as being configured so that electrons are directed toward the specimen at an oblique angle of incidence and scattered from the specimen at another oblique angle, the electron beam may be directed toward the specimen and scattered from the specimen at any suitable angle. Additionally, the electron beam subsystem may be configured to use multiple modes to generate an image of the specimen (e.g., using different illumination angles, collection angles, etc.), and the multiple modes may differ in any image generation parameter(s) of the subsystem.

[0042] The computer subsystem (124) may be coupled to the detector (134) as described above. The detector may detect electrons returned from the surface of the specimen, thereby forming an electron beam image of the specimen. The electron beam image may include any suitable electron beam image. The computer subsystem (124) may be configured to perform any of the functions described herein using the output of the detector and / or the electron beam image. The computer subsystem (124) may be configured to perform any additional step(s) described herein. A system including the imaging subsystem shown in FIG. 2 may also be configured as described herein.

[0043] FIGS. 1 and 2 are provided herein to generally illustrate the configuration of an imaging subsystem that may be included in the system embodiments described herein. Obviously, the configuration of the imaging subsystem described herein may be modified to optimize the performance of the system, as is typically done when designing commercial imaging systems. Additionally, the system described herein may be implemented using existing imaging systems, such as the 29xx and 39xx series tools commercially available from KLA Corp. of Milpitas, California (e.g., by adding the functions described herein to an existing inspection system). For some of these systems, the embodiments described herein may be provided as optional functions of the imaging system (e.g., in addition to other functions of the imaging system). Alternatively, the imaging subsystem described herein may be designed "from scratch" to provide a completely new imaging system.

[0044] Although the imaging subsystem is described above as an optical or electron beam-based subsystem, the imaging subsystem may be an ion beam-based subsystem. Such an imaging subsystem may be configured as illustrated in FIG. 2, except that the electron beam source may be replaced with any suitable ion beam source known in the art. Thus, the energy directed toward the specimen may contain ions. Additionally, the imaging subsystem may be any other suitable ion beam-based imaging subsystem, such as those included in commercially available focused ion beam (FIB) systems, helium ion microscopy (HIM) systems, and secondary ion mass spectroscopy (SIMS) systems.

[0045] The imaging subsystem described herein may be configured to generate an output of a specimen, e.g., an image, in a plurality of modes. Generally, a “mode” is defined by the value of a parameter of the imaging subsystem used to generate the output of the specimen and / or the image (or the output used to generate the image of the specimen). Thus, the modes may differ in the value for at least one of the parameters of the imaging subsystem (rather than the location on the specimen where the output is generated). For example, in an optical subsystem, different modes may use light of different wavelength(s) for illumination. The modes may differ in the illumination wavelength(s) as further described herein (e.g., by using different light sources, different spectral filters, etc. for different modes). In another example, different modes may use different illumination channels of the optical subsystem. For example, as mentioned above, the optical subsystem may include more than one illumination channel. In this way, different illumination channels may be used for different modes. The modes may also, or alternatively, differ in one or more acquisition / detection parameters of the optical subsystem. The modes may differ in any one or more modifiable parameters of the imaging subsystem (e.g., illumination polarization(s), angle(s), wavelength(s), etc., detection polarization(s), angle(s), wavelength(s), etc.). The imaging subsystem may be configured to scan specimens in different modes during the same scan or different scans, for example, depending on the ability to use multiple modes to scan specimens simultaneously.

[0046] In a similar manner, an electron beam subsystem can generate images with two or more different values ​​of its parameters. Multiple modes of the electron beam subsystem can be defined by the values ​​of the electron beam subsystem parameters used to generate images of the specimen. Thus, the modes may differ in the values ​​for at least one of the electron beam parameters of the electron beam subsystem. For example, different modes may use different angles of incidence for illumination.

[0047] As mentioned above, the imaging subsystem may be configured to scan energy (e.g., light, electron, etc.) across a physical version of the specimen and thereby generate an image of the physical version of the specimen. In this way, the imaging subsystem may be configured as a "real" subsystem rather than a "virtual" subsystem. However, the storage medium (not shown) and computer subsystem(s) (102) illustrated in FIG. 1 may be configured as a "virtual" system. In particular, the storage medium and computer subsystem(s) may be configured as a "virtual" inspection system as described in the commonly assigned U.S. Patent No. 8,126,255, registered to Bhaskar et al. on February 28, 2012, and U.S. Patent No. 9,222,895, registered to Duffy et al. on December 29, 2015, which are all incorporated by reference as fully presented herein. The embodiments described in this specification may also be configured as described in these patents.

[0048] A computer subsystem is configured to acquire a region of interest image of a specimen from one or more of the images generated by an imaging subsystem, as illustrated in step (300) of FIG. 3. The specimen may be a patterned wafer provided by a customer or user for inspection. The user may select optics to be used on the inspection platform to generate an image of the specimen. Acquiring a region of interest image may involve simply generating an image of the specimen using the imaging subsystem described herein. However, acquiring a region of interest image may be performed without an imaging subsystem. For example, the region of interest image may be acquired from a storage medium (such as one of those further described herein) in which the region of interest image is stored by another system or method.

[0049] In any of these cases, the region of interest image may simply comprise an image of the specimen generated by a detector of the imaging subsystem. However, as further described herein, acquiring the region of interest image may involve generating the region of interest image from two or more images generated by the detector(s) of the imaging subsystem. The detector images used to acquire the region of interest image may be generated as further described herein.

[0050] The area of ​​interest may be selected as the entire die or regions of interest (one or more) where systematic noise features are observed. For example, the user or computer subsystem may select the area of ​​interest of the specimen as a die, field, cell, region (e.g., a logic region within a logic device design or a memory region within a memory device design), a region where a specific feature of interest is formed, or even a region expected to contain only a single feature or only a few features (2 to 10 features). The area of ​​interest may also include any number of these regions. In this way, the area of ​​interest may vary depending on the region where the CA is set (e.g., for the entire die, or only for a specific region or part of the die having unique features, etc.). The user or computer subsystem may also select one or more parameters of the imaging subsystem (e.g., channels) and one or more dies from the available sample plans of the specimen to be used to acquire (grab) the image. While some embodiments may be described herein with respect to the region of interest of the die, the embodiments are applicable to any other region of interest described herein.

[0051] However, more generally, the term “region of interest” refers to the area of ​​the image used in the embodiments described herein. The region of interest may correspond to an area within the design for the specimen as described above. The region of interest may also, or alternatively, be determined based on inspection recipe parameters. For example, the region of interest may be a frame image generated by the imaging subsystem, a job of the frame image to be processed collectively during defect detection, a swath or sub-swath of the image generated during the scanning of the specimen, and similar. Thus, the size of these images may vary depending on the configuration of the imaging subsystem used for inspection and may vary depending on the image processing parameters used with the images.

[0052] The term “region of interest image” as used herein simply refers to an image of a region of the specimen used for CA setting in the steps described herein. Clearly, the CA setting steps described herein may then be performed separately and independently for multiple regions of interest on the specimen, and any CA set for different regions of interest may be combined into a single set of CAs for runtime inspection of the specimen.

[0053] In one embodiment, acquiring a region of interest image involves superimposing two or more images of the specimen corresponding to the region of interest on the specimen, which are generated by the imaging subsystem. This step may be performed to reduce (or even minimize) variations not associated with defects within the image that could otherwise distort the CA. For example, the segmentation described herein may be performed on a die basis. In such cases, two or more die images may be merged for the purpose of reducing, even minimizing, or eliminating inter-die variations (such as color variations that could affect the segmentation described herein). In one such example, scattered light images may be collected from two or more dies on the specimen and superimposed to reject inter-die variations. However, superimposed images may be generated for any other region of interest described herein. More generally, superimposed images should be generated for different instances of the same part of the design formed on the specimen.

[0054] Image superposition can be performed by aligning two or more images with one another using any suitable alignment method or algorithm known in the art. Once the images are aligned, they can be combined in any suitable manner so that similarity between the images is amplified (or at least maintained) and differences are simultaneously reduced. For example, the superimposed image can be generated by averaging the signals at the corresponding pixels of each of the images being superimposed, thereby maintaining the common signals in the images while suppressing the different signals. Unlike images that can be merged as further described herein to generate a true picture of the specimen structure on the specimen, the superimposed image can be generated with the same imaging subsystem parameters (i.e., the same mode).

[0055] The overlay step may generate an image that is subsequently merged with another image generated with different imaging subsystem parameters to create an actual picture of the specimen structure. As further described herein, any of the images being merged may be such an overlay image. In other words, an image generated with the same imaging parameters and corresponding to the same region within the design for the specimen may be overlaid, and then merged with another overlay image generated from another image that also corresponds to the same region within the design but was generated with different imaging parameters.

[0056] The image overlay step may also reduce any defect signal within any of the individual images being overlaid, but this is not the primary reason for performing this step. Generally, the images used for the steps described herein may be relatively clean, that is, relatively defect-free. Otherwise, or if the defect level of the image is unknown, the embodiment may be configured to prevent defects on the specimen from being designated as CA by performing a step in which any polygon found by detecting edges is compared to one or more size thresholds after the edge detection step further described herein. The size threshold(s) may be set by the user or computer subsystem based on any general knowledge of the specimen design, such as the general critical dimension of the technical node of the device being formed on the specimen. The size thresholds may be set such that one is smaller than the smallest of the patterned structures on the specimen layer to be inspected and the other is larger than the largest of the patterned structures. In this way, any defect smaller or larger than the patterned structure formed on the specimen may not be incorrectly detected as a specimen structure by the embodiments described herein and may not be incorrectly designated as CA.

[0057] In another embodiment, acquiring a region of interest image involves merging two or more images of a specimen corresponding to a region of interest on the specimen, which are generated with different parameters of the imaging subsystem. For example, images generated with different inspection subsystem parameters may be merged to generate a near-true image of the die and to ensure that all parts of all features are found during CA setup. In this way, the embodiment can acquire a true image of the die (feature) for the inspection platform.

[0058] In one such example, FIG. 4 illustrates a simplified schematic diagram of a die (400) in which two specimen structures (402 and 404) are depicted. The die (400) is depicted in FIG. 4 as it may be represented in the design for the specimen. Thus, the die (400) depicted in FIG. 4 may be a design image for the specimen. Depending on how accurately the design is fabricated on the specimen, the die (400) may also indicate how the specimen structures are formed on the specimen. Clearly, the specimen structures depicted in FIG. 4 do not represent any specimen structures that may actually be formed on the specimen described herein. Instead, the specimen structures depicted in FIG. 4 are intended merely to enhance understanding of the embodiments described herein.

[0059] Images of a die generated separately with different imaging subsystem parameters may have some significant differences. For example, an image (406) generated with a first set of imaging subsystem parameters contains only an image (408) of the specimen structure (402). Additionally, an image (410) generated with a second set of imaging subsystem parameters different from the first set of imaging subsystem parameters contains only an image (412) of the specimen structure (404). In this way, if only one of these images is used for CA setup, either the specimen structure (402) or the specimen structure (404) will not be considered in the CA setup process. However, merging the images (406 and 410) generates a merged image (414) containing an image (416) of the specimen structure (402) and an image (418) of the specimen structure (404). Thus, merging images generated with different imaging subsystem parameters can provide a more accurate representation of the specimen structure formed on the specimen. For example, as illustrated in FIG. 5, merging images (406 and 410) into a merged image (414) can be performed in the actual picture generation step (500) of the die.

[0060] Generally, merging preferably includes an alignment step so that the images being merged are accurately aligned with each other. The alignment may include any suitable alignment known in the art. Once the images are aligned, merging may simply involve summing the images through some additive function so that the intensities of the different images are added at each aligned pixel. Merging may also include more sophisticated steps. For example, merging may be performed on raw images generated by the detector(s) of the imaging subsystem. Alternatively, some image processing may be performed on the images prior to the actual merging step. Image processing may include, for example, the imaging superposition described above, low-pass filtering to attempt to minimize background noise within the image, high-pass filtering to attempt to minimize any defects or foreign matter that may scatter more strongly than specimen features, and any other image processing that may be performed during the inspection process. Image processing may also include a type of defect detection (based on the size and / or shape of features within the image rather than the actual difference between the test image and one or more reference images) to attempt to minimize the possibility that any defect may be incorrectly detected as part of the specimen structure. For example, a computer subsystem may determine whether any irregularly shaped features are visible within the image (such as when foreign matter is present on the specimen) and may remove signals corresponding to any such features before merging.

[0061] In one such embodiment, different parameters include different acquisition channels of the imaging subsystem. In this example, the channels may include a lateral channel and an upper channel, which may be configured as described in relation to the imaging subsystem illustrated in FIG. 1. One or more acquisition channels of interest may be selected to acquire actual images of die features, for example, based on knowledge of available imaging subsystem parameters. For example, one imaging subsystem channel may be known to be particularly suitable for imaging a horizontally oriented specimen structure, and another channel may be particularly suitable for imaging a vertically oriented specimen structure. Thus, these channels may be selected to generate a merged image to increase the probability that both the horizontally oriented specimen structure and the vertically oriented specimen structure are included within the merged image. In this way, scattered light images generated by the channels of interest may be superimposed to acquire actual images of die features.

[0062] In another embodiment, different parameters are selected to generate two or more images of a specimen having different aspects. For example, multiple acquisition channels may be used to obtain views of the specimen structure from different aspects. However, different aspects may be provided in a manner other than (or in addition to) different acquisition channels. For example, different aspects of the specimen and the specimen structure formed on the specimen may be provided by different illumination angles (polar angles and / or azimuths) and / or different polarization at either or both of illumination and acquisition. Appropriate parameters used to provide different aspects of the specimen structure may be selected, for example, based on any information available regarding the type of device being formed on the specimen and the hardware configuration available in the imaging subsystem.

[0063] In additional embodiments, different parameters include first and second parameters, and two or more of the images generated by different parameters include a first image generated by the first parameter and a second image generated by the second parameter, wherein the first image responds more to the first part of one or more specimen structures than to the second part of one or more specimen structures, and the second image responds to the second part of one or more specimen structures. Thus, different parameters may respond more to some specimen structures and less to others. An image referred to as "responsive" to a specimen structure as used herein is an image that shows the specimen structure at an intensity sufficiently different from the background image intensity so that it can be discovered by the steps described herein (e.g., segmentation step and edge detection step). Thus, an image responsive to a specimen structure may show the structure relatively faintly, as long as it is sufficiently different (brighter or darker) from the background for the purposes described herein.

[0064] If it is not a priori known that one imaging subsystem mode responds to all possible specimen structures on the specimen layer on which the CA is being set, more than one mode may be used to generate images, and the modes used for imaging may be selected based on their known ability to image a specific type of specimen structure. In this case, if one of the images responds more to the first specimen structure than to the second specimen structure, another of the images preferably responds to at least the second specimen structure (regardless of whether the image also responds to the first specimen structure).

[0065] In the example illustrated in FIG. 4, the parameters used to generate the specimen image (406) respond more to the specimen structure (402) than to the specimen structure (404) because the image (406) contains only the image (408) of the specimen structure (402). In contrast, the parameters used to generate the specimen image (410) respond more to the specimen structure (404) than to the specimen structure (402) because the image (410) contains only the image (412) of the specimen structure (404). Although these images are depicted as responding to only one specimen structure and not to another specimen structure at all, the images may also respond to all specimen structures to some extent, if not sufficiently (e.g., when the specimen structure image is not simply completely missing as shown in images (406 and 410), but is shown within the image but is difficult to distinguish from the noise within the image).

[0066] In an additional embodiment, merging images produces a merged image that is more similar to the design of one or more specimen structures than to one of two or more of the images. For example, as illustrated in FIG. 4, the merged image (414) is more similar to the die (400) than to either of the images (406 and 410). The increased similarity between the merged image (414) and the die (400) is due to the additive nature of the merging step performed as illustrated in step (500) of FIG. 5 to produce an actual picture of the die.

[0067] In some embodiments, different parameters are independent of the parameters of the imaging subsystem used for inspecting the specimen. For example, it is possible to use different acquisition channels for runtime inspection and CA setup image acquisition. In one such example, the inspection platform may include a microscope used to acquire die feature images for CA setup, and another acquisition channel may be used for inspection during runtime. Additionally, the image used for CA setup may be generated in more modes than the image used for runtime inspection. For example, as further described herein, different modes may be more or less responsive to a specific specimen structure. When it is unclear what type of specimen structure is formed on the specimen (as is expected in most cases in the embodiments described herein, since the design does not depend on specimen information), it may be advantageous to attempt multiple different modes to generate the image used for CA setup. Different modes may include more than is practical for use in inspection and may not be necessary for inspection. However, to ensure that all specimen structures on the specimen are found during the CA setup, more (and even more) modes may be used for image generation during the CA setup rather than during the inspection runtime. In this way, the image merging step may involve merging more than two images and as many images as the number of modes used during the CA setup.

[0068] These images may, in some cases, be used to select the mode used for runtime inspection. For example, if imaging subsystem parameters suitable for inspecting the specimen have not yet been established, the images generated for CA settings in the embodiments described herein may also be used to set hardware parameters for runtime inspection. In a similar manner, images may be used to set any image processing and / or defect detection parameters for runtime inspection. However, in any case, the imaging subsystem mode used for CA settings may be independent of the mode used for runtime inspection. In particular, since the mode suitable for CA settings is a mode sensitive to the specimen structure on the specimen and the mode suitable for runtime inspection is a mode sensitive to defects on the specimen, the mode suitable for CA settings may differ from the mode suitable for runtime inspection. Therefore, the mode used for CA settings described herein may be selected independently of any runtime inspection mode.

[0069] The acquired specimen images used for CA setup may differ from the images used for inspection setup and / or runtime inspection because they are used for different purposes. For example, images generated for CA setup generally need to respond to the specimen structures formed on the specimen, in that when combined, the images show all the specimen structures formed on the specimen. However, images suitable for inspection do not necessarily need to include images of patterned features formed on the specimen. For example, test and reference images of the same area in the design of the specimen may be acquired, and the reference image may be subtracted from the test image to generate a difference image, thereby offsetting commonalities within the images so that differences between the images can be identified as potential defects in the difference image. Therefore, test and reference images of patterned features do not need to show the patterned features to be suitable for detecting differences between images that can respond to defects on or near the patterned features. Thus, inspection images may or may not respond to the specimen structures, provided they respond to defects on the specimen.

[0070] In this manner, the CA can be established as described herein using an image showing a specimen structure on the specimen. Once the CA is established, it can be used to locate the CA in a runtime inspection image, regardless of whether the image shows the specimen structure. For example, based on location information determined for the CA (e.g., the CA location relative to a reference location such as a die corner) as further described herein, the CA can be found in the inspection image regardless of how the specimen structure appears in the inspection image. Thus, the image obtained and used for establishing the CA by the embodiment described herein may differ from, and even substantially differ from, the image used for inspection.

[0071] A computer subsystem is configured to separate a region of interest image into pixels corresponding to one or more specimen structures within the region of interest having different intensities from other pixels within the region of interest image by segmenting the region of interest image based on the intensity of pixels within the region of interest image, as illustrated in step (302) of FIG. 3. This segmentation step may be performed to display pixels and associated features using intensity-based segmentation. For example, the segmentation step separates specimen structures based on their differential scattering intensities. In this way, the embodiment described herein uses the differential intensities of specimen structures to generate CAs for inspection. A user may input a threshold used for this step so that pixels / features can be displayed and used for other steps described herein. In the example illustrated in FIG. 4, intensity-based segmentation can be applied to a merged image (414) (in the segmentation step (502) illustrated in FIG. 5), thereby generating a segmented image (420) in which pixels (422) corresponding to the specimen structure (402) and pixels (424) corresponding to the specimen structure (404) are separated from each other and from other pixels within the image.

[0072] In one embodiment, the segmentation step includes median-based segmentation. FIG. 6 schematically illustrates how median-based segmentation can be performed. As illustrated in FIG. 6, median-based segmentation (600) can be performed on an acquired region of interest image (602) containing images of specimen structures (604, 606, and 608). As with other images described herein, the specimen structures illustrated in FIG. 6 are not intended to show any specific specimen structures that may actually be formed on the specimens described herein, but are intended merely to enhance understanding of the embodiments described herein. Then, median-based segmentation can find the median of the intensity as a function of the number of pixels, which is schematically illustrated in plot (610). A threshold T0 for segmentation illustrated in this plot can be set to separate pixels into pixels above the threshold and pixels below the threshold based on the median intensity, as further described herein.

[0073] In another embodiment, the segmentation step includes projection-based segmentation. Projection-based segmentation is also schematically illustrated in FIG. 6. As illustrated in FIG. 6, projection-based segmentation (612) may be performed on an acquired region of interest image (614) containing an image of a specimen structure (616). Projection-based segmentation may include plotting the value of intensity as a function of position in the X direction, as illustrated in plot (618) in this case. A threshold T1 for segmentation illustrated in this plot may be set to separate pixels into pixels having an intensity above the threshold and pixels having an intensity below the threshold, as further described herein.

[0074] In some embodiments, the segmentation step includes applying a segmentation method to the region of interest image, displaying the result of the segmentation method to the user, receiving a cutline threshold for separation from the user, and performing separation using the cutline threshold. For example, the computer subsystem may apply the segmentation method as described above and then display pixel intensity and intensity-based segmentation results for the specimen (e.g., plot (610 or 618)). The user may be able to segment the region of interest image using the threshold. In particular, displaying the result to the user as described above may help the user determine an appropriate cutline for segmentation. While providing this information to the user may not be necessary, the user may find it relatively difficult to set the cutline threshold without this information. In this way, the embodiments described herein provide user flexibility. Then, separating pixels using the cutline threshold may be performed in any appropriate manner. Then, the computer subsystem may export the image after segmentation along with pixel information (x, y position relative to the die origin).

[0075] A computer subsystem is configured to detect edges of one or more specimen structures within a region of interest image based on pixels corresponding to one or more specimen structures, as illustrated in step (304) of FIG. 3. This step may be performed using an image exported by a segmentation step. Edge detection may be performed to find x, y coordinates for each polygon, which can then be used to generate CA as further described herein.

[0076] In one embodiment, detecting edges includes applying a binary mask to a segmented region of interest image to generate a binary image of one or more specimen structures, as illustrated in the binary mask and edge detection step (504) of FIG. 5, and detecting edges of one or more specimen structures within the binary image. For example, after the relevant pixels and corresponding polygons are marked using a segmentation threshold, the computer subsystem may apply a binary mask that sets pixels above the threshold to a maximum value and pixels below the threshold to a minimum value. In other words, detecting edges may include marking the features as polygons and using a binary mask in which pixels above the threshold are set to a maximum value and pixels below the threshold are set to a minimum value. Then, the edge detection method or algorithm may be applied to record an end point for a die corner or another suitable reference location.

[0077] In the example illustrated in FIG. 4, a binary mask can be applied to a segmented image (420) to generate a binary image (426) comprising a binary image feature (428) corresponding to a specimen structure (402) and a binary image feature (430) corresponding to a specimen structure (404). Obviously, the binary image may, in reality, be a black and white image, or at least an image in which the binary features appear as solid black. The binary features are not depicted as solid black in FIG. 4 because solid black areas are not recommended in the patent drawings. Then, edge detection can be performed using the binary image (426).

[0078] Applying a binary mask as described above is not required for the embodiments described herein, but in some cases, it may improve the results produced by the embodiments. For example, the embodiments may advantageously apply a binary mask (setting pixels above a threshold to a maximum value and pixels below a threshold to a minimum value) to facilitate the application of an edge detection method or algorithm for marking polygon endpoints (e.g., for die corners) as further described herein. In this way, binary masking may help improve the edge detection step performed to identify specimen structure(s) and determine information (such as coordinates) about the specimen structure(s) for other steps described herein. However, the edge detection step may be performed using any suitable edge detection method or algorithm known in the art, and some of these methods and systems may benefit more from the binary masking step than others.

[0079] A computer subsystem is configured to determine one or more characteristics of one or more CAs within an image of a specimen based on detected edges, as illustrated in step (306) of FIG. 3. In one embodiment, determining one or more characteristics includes identifying one or more endpoints of a specimen structure within an image of a region of interest based on detected edges and determining one or more characteristics based on the identified endpoints. For example, as described above, an edge detection method or algorithm may record endpoints of a specimen structure for die corners, for example, as illustrated in the binary image (426) illustrated in FIG. 4. Then, the computer subsystem may use these endpoints as characteristics of one or more CAs. For example, as illustrated in step (506) of FIG. 5, the computer subsystem may use the coordinates of endpoints within the binary image to generate CAs. The computer subsystem can also determine additional or other characteristics of CA(s), such as die corner relative coordinates, size, shape, etc., that can be determined for a specimen structure within an image from any other information determined by the recorded endpoints and / or detected edges. Then, the XY coordinates of these polygons and any of the other information described above can be used to generate a CA for inspection. In this way, the computer subsystem can use the reported endpoints to generate a customized CA.

[0080] In the example illustrated in FIG. 4, identifying endpoints can be performed using a binary image (426). In this example, endpoints may be two opposing corners of a binary feature (one of these corners is indicated by reference number (432) in FIG. 4). Endpoints may be recorded as (x, y) coordinates and can be used to generate CAs. For example, endpoint coordinates determined for a binary image feature (428) may include (x1, y1) and (x2, y2) shown in FIG. 4 at opposing corners of the image feature. Similarly, endpoint coordinates determined for a binary image feature (430) may include (x3, y3) and (x4, y4) shown in FIG. 4 at opposing corners of this image feature. These coordinates may also be determined for a die corner indicated by the (0,0) coordinate in FIG. 4, which may be identified in any suitable manner in any of the images described herein. Then, the endpoint, its coordinates, and any other information determined by the embodiments described herein may be used to specify different CAs for different specimen structures, such as CA (436) for specimen structure (402) and CA (438) for specimen structure (404), as shown in image (434).

[0081] In one embodiment, one or more specimen structures are sources of systematic noise within the image of the specimen generated for the inspection of the specimen. For example, die-based features may be sources of systematic noise (meaning that die-based features can cause noise within the image in a systematic manner rather than randomly), and the CA generated by the embodiments described herein can help suppress such noise. In particular, the CA for these features may be assigned a relatively high threshold (for reduced sensitivity) or assigned to a Do Not Care area (so that they are not inspected at all). In this way, the refined CA generated by the embodiments described herein can help the inspection platform reduce the nuisance rate by reducing the amount of systematic noise that is incorrectly detected as potential defects. Reducing the nuisance rate increases the likelihood of finding actual defects and reduces the scanning electron microscope (SEM) defect review loading for the inspection tool user.

[0082] While generating a CA for the purpose of reducing systematic noise from a specimen structure is one particularly advantageous use of the embodiment described herein, the embodiment may be used to set a curated CA for any other purpose of inspection. In this way, the CA generated as described herein may be used for optimal inspection in a number of ways. If the specimen structure is a noise source, a colder (higher) defect detection algorithm threshold may be set for the CA generated for the specimen structure, and accordingly, the specimen structure is inspected with reduced sensitivity. If the specimen structure is or is included in a region of interest, inspection may be performed with a hotter (lower) defect detection algorithm threshold for the CA generated for the specimen structure, and thus the specimen structure is inspected with higher sensitivity. The CA set for the specimen structure may also be marked as a do not inspect area where appropriate. In addition, the embodiments described in this specification can be equally applied to all inspection platforms (DF or BF, even though the inventor demonstrated functionality using DF as an example) and to both the advanced technology node layer and the legacy node layer.

[0083] A CA established as described herein may also include different types of CA for a single specimen. For example, obvious, specimens such as those described herein often have different types of specimen structures formed on the same layer. Accordingly, an image of a specimen generated from an inspection of a single layer may include images of different types of specimen structures. Examples of these different types of specimen structures include, but are not limited to, contact holes, isolated line-type structures, dense line / space structures, and larger structures such as dummy features and alignment marks. Some of these structures may be more important than others, while others may not be of interest at all. Therefore, when different types of specimen structures are included in the inspection image, different types of CA may be appropriate.

[0084] Information regarding different types of CA can be obtained from the results of the embodiments described herein. For example, the results of the edge detection step can be used to determine information such as the size, shape, and location of specimen structures within the design for the specimen. General information regarding specimen structures having these characteristics can be used to determine appropriate inspection parameters for the specimen structures. For example, dense line / space structures are generally significantly important, but alignment marks are not. Therefore, dense line / space structures may be inspected with a defect detection threshold more sensitive than alignment mark structures. In another example, dummy structures may not be of interest at all and may therefore be designated as uncared-for areas. Accordingly, a computer subsystem may be configured to use this general information to determine or suggest different inspection parameters for different structures discovered by the embodiments described herein.

[0085] The computer subsystem may also be configured to display information about the discovered specimen structures to the user and to provide means for the user to set a CA type and / or one or more inspection parameters for each specimen structure (or one or more of the specimen structures). For example, the computer subsystem may be configured to display a binary image, such as a binary image (426), to the user, along with optionally any other information determined for the specimen structures. The computer subsystem may also display proposed CA type(s) and / or one or more proposed inspection parameters to the user, which may then be accepted, rejected, or modified by the user. The computer subsystem may also, or alternatively, provide a user interface (UI) that may provide different ways for the user to input CA type(s) and / or inspection parameters for the discovered specimen structures. The computer subsystem may also group any one or more instances of CAs to be inspected with the same type and the same inspection parameters into a CA group (CA group; CAG) which may, in some cases, simplify runtime inspection behavior.

[0086] In some embodiments, the imaging subsystem is configured to generate an image of the specimen by detecting light scattered from the specimen, and one or more specimen structures scatter light more strongly than defects on the specimen. For example, the embodiments described herein are particularly suitable for generating detailed CA for relatively bright specimen features on a patterned wafer. Such CA may be treated as a noise source, processed according to inspection requirements (inspected more sensitively or less sensitively), or marked as an uninspected area (i.e., uncared-for area or non-CA). Since these features generally scatter more strongly than the background (and are therefore brighter in the DF tool), they may be marked based on differential scattered light intensity as further described herein.

[0087] In additional embodiments, the computer subsystem is configured to perform the steps of acquiring, segmenting, detecting, determining, and storing without information regarding the design of the specimen. In particular, as further described herein, the embodiment operates based on an intensity differential and does not require access to a design file for any reason. In other words, the embodiment described herein can be performed using only the image of the specimen generated by the inspection subsystem (it may be possible to use it in conjunction with some input from the user as further described herein). Accordingly, the embodiment is particularly advantageous for CA setups when one entity owns the design for the specimen and another entity sets up the inspection process for the specimen, which is a situation commonly encountered today.

[0088] The computer subsystem is also configured to store information about one or more CAs for use in inspecting a specimen, as illustrated in step (308) of FIG. 3. For example, the computer subsystem may generate a CA file, which may have any suitable file format or extension, such as a .bin file. The information about one or more CAs may include any suitable information, such as CA location and size. During inspection, a tool performing the inspection, which may or may not include the imaging subsystem and computer subsystem described herein, may automatically generate a CA having dimensions and location specified by the stored information. In some of these cases, the inspection tool may bring the stored information or its representation into the CA UI within the main UI of the inspection tool, thereby enabling the user of the tool to gain an understanding of the information.

[0089] The computer subsystem may also be configured to store CA information in a recipe, or to generate a recipe for an inspection in which the CA will be used. As the term is used herein, a “recipe” is defined as a set of instructions that can be used by a tool to perform a process on a specimen. In this way, generating a recipe may include generating information on how the process is performed, which can then be used to generate instructions for performing the process. The information regarding the CA stored by the computer subsystem may include any information (e.g., filename and location where it is stored) that can be used to identify, access, and / or use the selected CA. The information regarding the stored CA may also include actual code, instructions, algorithms, etc., for applying the CA and detecting defects based on the applied CA.

[0090] A computer subsystem may be configured to store information about CA on any suitable computer-readable storage medium. The information may be stored together with any of the results described herein and may be stored in any manner known in the art. The storage medium may include any storage medium described herein or any other suitable storage medium known in the art. After the information is stored, the information may be accessed from the storage medium and used by any of the method or system embodiments described herein, formatted for display to a user, or used by another software module, method, or system, etc. For example, an embodiment described herein may generate an inspection recipe as described above. Then, said inspection recipe may be stored and used by a system or method (or another system or method) to inspect a specimen or another specimen (of the same layer), thereby generating information about the specimen or another specimen (e.g., defect information).

[0091] A computer subsystem may be configured to perform defect detection in an inspection process using CAs configured as described herein. For example, an imaging subsystem described herein may be configured to generate a test image of a specimen during the inspection process. CAs may be found in the test image using information regarding CAs described herein. Then, the computer subsystem may perform defect detection based on information regarding CAs (and it may be possible to ignore any uncared-for areas). For example, the computer subsystem may subtract a reference image from the test image and thereby generate a difference image. Defect detection may also include applying a threshold to the difference image, which may be generally referred to in the art as a defect detection threshold. The threshold used for defect detection performed in any of the CAs may be determined as described herein (e.g., more sensitive for CAs requiring more sensitive inspection and less sensitive for CAs requiring less sensitive inspection). Any image signal or data having a value exceeding a threshold within the difference image may be identified as a defect or potential defect by the computer subsystem. All other image signals or data within the difference image may not be identified as defects or potential defects.

[0092] Of course, this is perhaps the simplest version of how defect detection can be performed using the result of subtracting a reference image from a test image. The embodiments described herein are not limited to the test image and the reference image and the defect detection method or algorithm that can be used. For example, when a reference image is subtracted from a test image, there are many different types of defect detection methods or algorithms that can be used to detect defects or potential defects in the resulting difference image. Any or all of these defect detection methods or algorithms may be used in the embodiments described herein, and an appropriate method or algorithm may be selected based on information regarding the specimen.

[0093] Results and information generated by performing inspections on a specimen or other specimens of the same type may be used in various ways by the embodiments and / or other systems and methods described herein. Such functions include, but are not limited to, modifying processes such as manufacturing processes or steps performed or to be performed on the inspected specimen or another specimen in a feedback or feedforward manner. For example, the computer subsystem described herein may be configured to determine one or more modifications to the process performed on the inspected specimen and / or to be performed on the specimen as described herein, based on detected defect(s). Modifications to the process may include any suitable modifications to one or more parameters of the process. The computer subsystem preferably determines such modifications so that defects may be reduced or prevented in another specimen where the revised process is performed, defects may be corrected or eliminated in another process performed on the specimen, defects may be compensated in another process performed on the specimen, and so on. The computer subsystem described in this specification may determine such changes in any suitable manner known in the art.

[0094] Then, these changes may be transferred to a semiconductor fabrication system (not shown) or a storage medium (not shown) accessible to the computer subsystem and semiconductor fabrication system described herein. The semiconductor fabrication system may or may not be part of the system embodiment described herein. For example, the system described herein may be coupled to the semiconductor fabrication system through one or more common elements, such as, for example, a housing, a power supply, a specimen handling device or mechanism. The semiconductor fabrication system may include any semiconductor fabrication system known in the art, for example, a lithography tool, an etching tool, a chemical-mechanical polishing (CMP) tool, a deposition tool, and similar ones.

[0095] Accordingly, as described herein, the embodiments may be used to establish a new inspection process or recipe. The embodiments may also be used to modify an existing inspection process or recipe, regardless of whether it is an inspection process or recipe that was used on a specimen or an inspection process or recipe that was created for one specimen and is being adapted for another specimen. Furthermore, the embodiments described herein are not limited only to the creation or modification of CA. For example, the embodiments described herein may also be used to select one or more other parameters for inspection, such as a mode performed based on the systematic noise source identified by the embodiments described herein, output processing parameters such as defect detection sensitivity to be used in the systematic noise source region versus another region, and any other parameters of the inspection process for which CA was established as described herein.

[0096] The embodiments described herein provide numerous advantages in addition to those already described, compared to previously used methods and systems for establishing CAs for inspection processes. For example, the embodiments described herein can advantageously reduce the time required for recipe generation. Furthermore, the embodiments described herein can be used to generate refined CAs specialized for die-based features, and these refined CAs can improve the sensitivity of the inspection and help capture more key DOIs, which consequently improves customer yield. The embodiments described herein also provide improved ease of use. For example, the user can acquire only the die image(s) using the inspection optical system and adjust the segmentation parameters as desired. The x, y coordinates (recorded by the edge detection step) can be used to generate the required CA. Thus, the embodiments also reduce the need for expertise in design-based CA algorithms and methods.

[0097] Each of the embodiments of the system described above can be combined together into a single embodiment.

[0098] Another embodiment relates to a computer-implemented method for setting CAs for inspecting a specimen. The method comprises the steps of acquiring a region of interest image as described above, segmenting the region of interest image, detecting edges, determining one or more characteristics of CA(s) within the image, and storing information.

[0099] Each step of the method may be performed as further described herein. The method may also include any other step(s) that may be performed by the imaging subsystem, computer subsystem, and / or system described herein. Steps of the method are performed by a computer subsystem coupled to the imaging subsystem, all of which may be configured according to any of the embodiments described herein. Additionally, the method described above may be performed by any of the system embodiments described herein.

[0100] Additional embodiments relate to a non-transient computer-readable medium storing program instructions executable on a computer system for performing a computer-implemented method for setting up CA for testing a specimen. One such embodiment is illustrated in FIG. 7. In particular, as illustrated in FIG. 7, the non-transient computer-readable medium (700) includes program instructions (702) executable on a computer system (704). The computer-implemented method may include any step(s) of any method(s) described herein.

[0101] Program instructions (702) for implementing a method such as that described in this specification may be stored in a computer-readable medium (700). The computer-readable medium may be a storage medium such as a magnetic disk or optical disk, a magnetic tape, or any other suitable non-transient computer-readable medium known in the art.

[0102] Program instructions may be implemented using any of the various methods, including, among others, procedure-based techniques, component-based techniques, and / or object-oriented techniques. For example, program instructions may be implemented using ActiveX controls, C++ objects, JavaBeans, Microsoft Foundation Classes ("MFC"), Streaming SIMD Extension (SSE), or other technologies or methodologies as desired.

[0103] The computer system (704) may be configured according to any of the embodiments described in this specification.

[0104] Further modifications and alternative embodiments of various aspects of the invention will be apparent to a person skilled in the art by taking into account this description. For example, a method and system for establishing a CA for inspecting a specimen are provided. Accordingly, this description should be interpreted only as illustrative and is intended to teach a person skilled in the art a general manner of practicing the invention. It should be understood that the forms of the invention shown and described herein should be considered as currently preferred embodiments. Elements and materials may be substituted for those exemplified and described herein, parts and processes may be reversed, and specific features of the invention may be utilized independently, all of which will be apparent to a person skilled in the art after benefiting from this description of the invention. Modifications may be made to the elements described herein without departing from the spirit and scope of the invention as described in the following claims.

Claims

Claim 1 A system configured to establish a care area for the inspection of a specimen, comprising: an imaging subsystem configured to generate an image of the specimen; and a computer subsystem, wherein the computer subsystem comprises: Acquiring a region of interest image of the specimen from one or more of the images generated by the imaging subsystem; By dividing the region of interest image based on the intensity of pixels within the region of interest image, the region of interest image is separated into pixels corresponding to one or more specimen structures within the region of interest image that have an intensity different from other pixels within the region of interest image; Detecting the edges of one or more specimen structures within the region of interest image based on the pixels corresponding to the one or more specimen structures; Determining one or more characteristics of one or more care regions within an image of the specimen based on the detected edges; and A system configured to store information about one or more care areas for use in inspecting the above specimen. Claim 2 A system according to claim 1, wherein acquiring the region of interest image comprises superimposing two or more of the images of the specimen corresponding to the region of interest on the specimen, which are generated by the imaging subsystem. Claim 3 A system according to claim 1, wherein acquiring the region of interest image comprises merging two or more images of the specimen corresponding to the region of interest on the specimen, generated with different parameters of the imaging subsystem. Claim 4 In paragraph 3, the system wherein the different parameters include different acquisition channels of the imaging subsystem. Claim 5 A system according to paragraph 3, wherein the different parameters are selected to generate two or more images of the specimen having different aspects. Claim 6 A system according to claim 3, wherein the different parameters include first and second parameters, and two or more of the images generated by the different parameters include a first image generated by the first parameter and a second image generated by the second parameter, wherein the first image is more responsive to the first part of the one or more specimen structures than to the second part of the one or more specimen structures, and the second image is responsive to the second part of the one or more specimen structures. Claim 7 A system according to paragraph 3, wherein the merging generates a merged image that is more similar to the design of one or more specimen structures than to one of two or more of the images. Claim 8 A system in which, in paragraph 3, the different parameters are independent of the parameters of the imaging subsystem used for the inspection of the specimen. Claim 9 A system according to claim 1, wherein the division includes median-based division. Claim 10 A system according to claim 1, wherein the division includes projection-based division. Claim 11 A system according to claim 1, wherein the segmenting comprises applying a segmentation method to the region of interest image, displaying the result of the segmentation method to a user, receiving a cutline threshold for the separation from the user, and performing the separation using the cutline threshold. Claim 12 A system according to claim 1, wherein detecting the edge comprises applying a binary mask to the segmented region of interest image to generate a binary image of the one or more specimen structures, and detecting the edge of the one or more specimen structures within the binary image. Claim 13 A system according to claim 1, wherein one or more specimen structures are sources of systematic noise within an image of the specimen generated for inspection of the specimen. Claim 14 A system according to claim 1, wherein the imaging subsystem is also configured to generate an image of the specimen by detecting light scattered from the specimen, and the one or more specimen structures scatter the light more strongly than defects on the specimen. Claim 15 In claim 1, the computer subsystem is also configured to perform the acquisition, segmentation, detection, determination, and storage without information regarding the design of the specimen. Claim 16 A system according to claim 1, wherein determining the one or more characteristics comprises identifying the end points of the one or more specimen structures within the region of interest image based on the detected edges, and determining the one or more characteristics based on the identified end points. Claim 17 A system according to claim 1, wherein the imaging subsystem is a light-based imaging subsystem. Claim 18 A system according to claim 1, wherein the imaging subsystem is an electronic-based imaging subsystem. Claim 19 A non-transient computer-readable medium storing program instructions executable on a computer system for performing a computer implementation method for establishing a care area for inspection of a specimen, wherein the computer implementation method comprises: acquiring a region of interest image for a specimen from one or more images of the specimen generated by an imaging subsystem; dividing the region of interest image based on the intensity of a pixel within the region of interest image to separate the region of interest image into pixels corresponding to one or more specimen structures within the region of interest image having an intensity different from other pixels within the region of interest image; detecting edges of one or more specimen structures within the region of interest image based on the pixels corresponding to the one or more specimen structures; determining one or more characteristics of one or more care areas within the image of the specimen based on the detected edges; and storing information about the one or more care areas for use in inspection of the specimen. Claim 20 A computer-implemented method for establishing a care area for inspection of a specimen, comprising: acquiring a region of interest image for a specimen from one or more images of the specimen generated by an imaging subsystem; dividing the region of interest image based on the intensity of pixels within the region of interest image to separate the region of interest image into pixels corresponding to one or more specimen structures within the region of interest image having an intensity different from other pixels within the region of interest image; detecting edges of one or more specimen structures within the region of interest image based on the pixels corresponding to the one or more specimen structures; determining one or more characteristics of one or more care areas within the image of the specimen based on the detected edges; and storing information about the one or more care areas for use in inspection of the specimen, wherein the acquiring, dividing, detecting, determining, and storing steps are performed by a computer subsystem coupled to the imaging subsystem.

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