IMAGE DENOISING FOR EXAMINATION OF A SEMICONDUCTOR SPECIMEN

    公开(公告)号:US20240153043A1

    公开(公告)日:2024-05-09

    申请号:US17983181

    申请日:2022-11-08

    Abstract: There is provided an image generation system and method. The method comprises obtaining a runtime image of a semiconductor specimen with a low Signal-to-noise ratio (SNR), and processing the runtime image using a machine learning (ML) model to obtain an output image with a high SNR. The ML model is previously trained using a training set comprising a plurality of low SNR images associated with a high SNR image. The plurality of low SNR images correspond to a plurality of sequences of frames acquired in a plurality of runs of scanning a first site of the specimen. The high SNR image is generated based on the plurality of low SNR images. The training comprises, for each low SNR image: processing the low SNR image by the ML model to obtain predicted image data, and optimizing the ML model based on the predicted image data and the high SNR image.

    THREE-DIMENSIONAL RECONSTRUCTION OF A SEMICONDUCTOR SPECIMEN

    公开(公告)号:US20220082376A1

    公开(公告)日:2022-03-17

    申请号:US17024578

    申请日:2020-09-17

    Abstract: There is provided a system and a method comprising obtaining a first (respectively second) image of an area of the semiconductor specimen acquired by an electron beam examination tool at a first (respectively second) illumination angle, determining a plurality of height values informative of a height profile of the specimen in the area, the determination comprising solving an optimization problem which comprises a plurality of functions, each function being representative of a difference between data informative of a grey level intensity at a first location in the first image and data informative of a grey level intensity at a second location in the second image, wherein, for each function, the second location is determined with respect to the first location, or conversely, when solving the optimization problem, wherein a distance between the first and the second locations depends on the height profile, and the first and second illumination angles.

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