Abstract: A method includes receiving one or more sets of wafer data, identifying one or more primitives from one or more shapes in one or more layers in the one or more sets of wafer data, classifying each of the one or more primitives as a particular primitive type, identifying one or more primitive characteristics for each of the one or more primitives, generating a primitive database of the one or more primitives, generating one or more rules based on the primitive database, receiving one or more sets of design data, applying the one or more rules to the one or more sets of design data to identify one or more critical areas, and generating one or more wafer inspection recipes including the one or more critical areas for an inspection sub-system.

Abstract: A method includes receiving one or more sets of wafer data, identifying one or more primitives from one or more shapes in one or more layers in the one or more sets of wafer data, classifying each of the one or more primitives as a particular primitive type, identifying one or more primitive characteristics for each of the one or more primitives, generating a primitive database of the one or more primitives, generating one or more rules based on the primitive database, receiving one or more sets of design data, applying the one or more rules to the one or more sets of design data to identify one or more critical areas, and generating one or more wafer inspection recipes including the one or more critical areas for an inspection sub-system.

Abstract: A method includes receiving one or more sets of wafer data, identifying one or more primitives from one or more shapes in one or more layers in the one or more sets of wafer data, classifying each of the one or more primitives as a particular primitive type, identifying one or more primitive characteristics for each of the one or more primitives, generating a primitive database of the one or more primitives, generating one or more rules based on the primitive database, receiving one or more sets of design data, applying the one or more rules to the one or more sets of design data to identify one or more critical areas, and generating one or more wafer inspection recipes including the one or more critical areas for an inspection sub-system.

Abstract: A method includes receiving one or more sets of wafer data, identifying one or more primitives from one or more shapes in one or more layers in the one or more sets of wafer data, classifying each of the one or more primitives as a particular primitive type, identifying one or more primitive characteristics for each of the one or more primitives, generating a primitive database of the one or more primitives, generating one or more rules based on the primitive database, receiving one or more sets of design data, applying the one or more rules to the one or more sets of design data to identify one or more critical areas, and generating one or more wafer inspection recipes including the one or more critical areas for an inspection sub-system.

Abstract: Methods and systems for identifying outliers in multiple instances of a pattern of interest (POI) are provided. One system includes one or more computer subsystems configured for acquiring images generated by an imaging subsystem at multiple instances of a POI within a die formed on the specimen. The multiple instances include two or more instances that are located at aperiodic locations within the die. The computer subsystem(s) are also configured for determining a feature of each of the images generated at the multiple instances of the POI. In addition, the computer subsystem(s) are configured for identifying one or more outliers in the multiple instances of the POI based on the determined features.

Abstract: Methods and systems for identifying outliers in multiple instances of a pattern of interest (POI) are provided. One system includes one or more computer subsystems configured for acquiring images generated by an imaging subsystem at multiple instances of a POI within a die formed on the specimen. The multiple instances include two or more instances that are located at aperiodic locations within the die. The computer subsystem(s) are also configured for determining a feature of each of the images generated at the multiple instances of the POI. In addition, the computer subsystem(s) are configured for identifying one or more outliers in the multiple instances of the POI based on the determined features.

Abstract: Methods and systems for determining a position of inspection data with respect to a stored high resolution die image are provided. One method includes aligning data acquired by an inspection system for alignment sites on a wafer with data for predetermined alignment sites. The predetermined alignment sites have a predetermined position in die image space of a stored high resolution die image for the wafer. The method also includes determining positions of the alignment sites in the die image space based on the predetermined positions of the predetermined alignment sites in the die image space. In addition, the method includes determining a position of inspection data acquired for the wafer by the inspection system in the die image space based on the positions of the alignment sites in the die image space.

Abstract: Systems and methods for generating information for use in a wafer inspection process are provided. One method includes acquiring output of an inspection system for die(s) located on wafer(s), combining the output for the die(s) based on within die positions of the output, determining, on a within die position basis, a statistical property of variation in values of characteristic(s) of the combined output, and assigning the within die positions to different groups based on the statistical properties determined for the within die positions. The method also includes storing information for the within die positions and the different groups to which the within die positions are assigned in a storage medium that is accessible to the inspection system for performing the wafer inspection process, which includes applying defect detection parameter(s) to additional output of the inspection system generated for a wafer based on the information thereby detecting defects on the wafer.

Abstract: Systems and methods for determining one or more parameters of a wafer inspection process are provided. One method includes aligning optical image(s) of an alignment target to their corresponding electron beam images generated by an electron beam defect review system. The method also includes determining different local coordinate transformations for different subsets of alignment targets based on results of the aligning. In addition, the method includes determining positions of defects in wafer inspection system coordinates based on coordinates of the defects determined by the electron beam defect review system and the different local coordinate transformations corresponding to different groups of the defects into which the defects have been separated. The method further includes determining one or more parameters for an inspection process for the wafer based on defect images acquired at the determined positions by a wafer inspection system.

Abstract: Methods and systems for determining a position of inspection data with respect to a stored high resolution die image are provided. One method includes aligning data acquired by an inspection system for alignment sites on a wafer with data for predetermined alignment sites. The predetermined alignment sites have a predetermined position in die image space of a stored high resolution die image for the wafer. The method also includes determining positions of the alignment sites in the die image space based on the predetermined positions of the predetermined alignment sites in the die image space. In addition, the method includes determining a position of inspection data acquired for the wafer by the inspection system in the die image space based on the positions of the alignment sites in the die image space.

Abstract: Systems and methods for generating information for use in a wafer inspection process are provided. One method includes acquiring output of an inspection system for die(s) located on wafer(s), combining the output for the die(s) based on within die positions of the output, determining, on a within die position basis, a statistical property of variation in values of characteristic(s) of the combined output, and assigning the within die positions to different groups based on the statistical properties determined for the within die positions. The method also includes storing information for the within die positions and the different groups to which the within die positions are assigned in a storage medium that is accessible to the inspection system for performing the wafer inspection process, which includes applying defect detection parameter(s) to additional output of the inspection system generated for a wafer based on the information thereby detecting defects on the wafer.

Abstract: Systems and methods for design-based inspection using repeating structures are provided.

Abstract: Methods and systems for adaptive sampling for semiconductor inspection recipe creation, defect review, and metrology are provided. The embodiments provide image processing and pattern recognition algorithms and an adaptive sampling method for extracting critical areas from SEM image patches for use in a wafer inspection system when design data for a semiconductor chip is not available. The embodiments also provide image processing and pattern recognition algorithms for efficiently discovering critical defects and significant deviations in the normal manufacturing process, using the output from a wafer inspection system and an adaptive sampling method to select wafer locations to be examined on a high resolution review or metrology tool.

Abstract: Systems and methods for determining one or more parameters of a wafer inspection process are provided. One method includes aligning optical image(s) of an alignment target to their corresponding electron beam images generated by an electron beam defect review system. The method also includes determining different local coordinate transformations for different subsets of alignment targets based on results of the aligning. In addition, the method includes determining positions of defects in wafer inspection system coordinates based on coordinates of the defects determined by the electron beam defect review system and the different local coordinate transformations corresponding to different groups of the defects into which the defects have been separated. The method further includes determining one or more parameters for an inspection process for the wafer based on defect images acquired at the determined positions by a wafer inspection system.

Abstract: Methods and systems for adaptive sampling for semiconductor inspection recipe creation, defect review, and metrology are provided. The embodiments provide image processing and pattern recognition algorithms and an adaptive sampling method for extracting critical areas from SEM image patches for use in a wafer inspection system when design data for a semiconductor chip is not available. The embodiments also provide image processing and pattern recognition algorithms for efficiently discovering critical defects and significant deviations in the normal manufacturing process, using the output from a wafer inspection system and an adaptive sampling method to select wafer locations to be examined on a high resolution review or metrology tool.

Abstract: Various embodiments for determining dynamic care areas are provided. In one embodiment, a first inspection process is performed on a wafer after a first fabrication step has been performed on the wafer and before a second fabrication process has been performed on the wafer. One embodiment includes determining care areas for a second inspection process based on inspection results generated by the first inspection process. The second inspection process will be performed on the wafer after the second fabrication step has been performed on the wafer.

Abstract: The present invention may include segmenting an image at a first resolution level and a second resolution level, wherein one or more parameters of a segmentation algorithm are trainable via user classification feedback, extracting features from a first plurality of segment primitives and a second plurality of segment primitives, wherein one or more parameters of a segment feature extraction algorithm are trainable via user classification feedback, building a first and second segmentation hierarchy by generating one or more clusters of the first plurality of segment primitives and the second plurality of segment primitives, extracting one or more features from the first segmentation hierarchy and the second segmentation hierarchy utilizing a hierarchy feature extraction algorithm, determining an inter-level relationship between the clusters generated for the first resolution level and the second level, and automatically classifying one or more tissue elements of the tissue specimen via a user-trained classific

Abstract: Systems and methods for design-based inspection using repeating structures are provided.

Abstract: Various embodiments for determining dynamic care areas are provided.

Abstract: A method of detecting anomalies in a test image. Test features of pixels within the test image are selected, and reference features of pixels within at least one reference image are also selected. A signal distribution of test features and reference features in a multi-dimensional feature space is created, and stored. Those test features of the test image that do not satisfy a set of criteria for normalcy are selected as candidate points. Those candidate points that are statistical outliers are identified as anomalies. Positions of the anomalies are located using the stored signal distribution within which the defects have been identified as a lookup table.