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IMAGE ALIGNMENT SETUP FOR SPECIMENS WITH INTRA- AND INTER-SPECIMEN VARIATIONS USING UNSUPERVISED LEARNING AND ADAPTIVE DATABASE GENERATION METHODS
IMAGE ALIGNMENT SETUP FOR SPECIMENS WITH INTRA- AND INTER-SPECIMEN VARIATIONS USING UNSUPERVISED LEARNING AND ADAPTIVE DATABASE GENERATION METHODS
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机译:使用无监督学习和自适应数据库生成方法的标本对标本的图像对齐设置和标本的变化
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摘要
Methods and systems for determining one or more alignment parameters for use in a process performed on a specimen are provided. One method includes determining measures of similarity between images generated by an imaging system for corresponding locations in each of two or more pairs of dies on a specimen and performing cluster analysis based on the determined measures of similarity to identify the images that are most similar to each other and to assign different subsets of the images that are most similar to each other to different die clusters, respectively. The method also includes separately determining one or more alignment parameters for two or more of the different die clusters. The one or more alignment parameters are used for aligning images generated by the imaging system for the specimen or another specimen to a common reference.
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