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公开(公告)号：US12288667B2
公开(公告)日：2025-04-29
申请号：US17831147
申请日：2022-06-02
Applicant: FEI Company
Inventor： Pavel Potocek , Bert Henning Freitag , Maurice Peemen
Abstract: A method of imaging a sample includes acquiring one or more first images of a region of the sample at a first imaging condition with a charged particle microscope system. The one or more first images are applied to an input of a trained machine learning model to obtain a predicted image indicating atom structure probability in the region of the sample. An enhanced image indicating atom locations in the region of the sample based on the atom structure probability in the predicted image is caused to be displayed in response to obtaining the predicted image.
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公开(公告)号：US20230395351A1
公开(公告)日：2023-12-07
申请号：US17831147
申请日：2022-06-02
Applicant: FEI Company
Inventor： Pavel Potocek , Bert Henning Freitag , Maurice Peemen
CPC classification number: H01J37/28 , H01J37/244 , H01J37/222 , H01J37/20 , H01J37/265 , G06T7/0004 , H01J2237/226 , G06T2207/10061 , G06T2207/20081
Abstract: A method of imaging a sample includes acquiring one or more first images of a region of the sample at a first imaging condition with a charged particle microscope system. The one or more first images are applied to an input of a trained machine learning model to obtain a predicted image indicating atom structure probability in the region of the sample. An enhanced image indicating atom locations in the region of the sample based on the atom structure probability in the predicted image is caused to be displayed in response to obtaining the predicted image.
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公开(公告)号：US11355305B2
公开(公告)日：2022-06-07
申请号：US16596538
申请日：2019-10-08
Applicant: FEI Company
Inventor： Remco Johannes Petrus Geurts , Pavel Potocek , Maurice Peemen , Ondrej Machek
IPC: H01J37/20 , H01J37/22 , G06N3/08 , H01J37/26 , H01J37/305
Abstract: Methods and systems for creating TEM lamella using image restoration algorithms for low keV FIB images are disclosed. An example method includes irradiating a sample with an ion beam at low keV settings, generating a low keV ion beam image of the sample based on emissions resultant from irradiation by the ion beam, and then applying an image restoration model to the low keV ion beam image of the sample to generate a restored image. The sample is then localized within the restored image, and a low keV milling of the sample is performed with the ion beam based on the localized sample within the restored image.
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公开(公告)号：US11151356B2
公开(公告)日：2021-10-19
申请号：US16287982
申请日：2019-02-27
Applicant: FEI Company
Inventor： John Flanagan , Erik Franken , Maurice Peemen
Abstract: Convolutional neural networks (CNNs) of a set of CNNs are evaluated using a test set of images (electron micrographs) associated with a selected particle type. A preferred CNN is selected based on the evaluation and used for processing electron micrographs of test samples. The test set of images can be obtained by manual selection or generated using a model of the selected particle type. Upon selection of images using the preferred CNN in processing additional electron micrographs, the selected images can be added to a training set or used as an additional training set to retrain the preferred CNN. In some examples, only selected layers of the preferred CNN are retrained. In other examples, two dimensional projections of based on particles of similar structure are used for CNN training or retraining.
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5.发明公开公开(公告)号：US20240281650A1
公开(公告)日：2024-08-22
申请号：US18171543
申请日：2023-02-20
Applicant: FEI Company
Inventor： Hans Vanrompay , Maurice Peemen
IPC: G06N3/08
CPC classification number: G06N3/08
Abstract: Disclosed herein are scientific instrument support systems, as well as related methods, apparatus, computing devices, and computer-readable media. Some embodiments provide a scientific instrument including detectors supporting two or more spectroscopic modalities and an imaging modality and further including an electronic controller configured to process streams of measurements received from the detectors. The electronic controller operates to generate a base image of the sample based on the measurements corresponding to the imaging modality and further operates to generate a cluster-mapped image of the sample based on the base image and further based on mappings of the measured spectra corresponding to different pixels of the base image to various clusters in the latent space of a variational autoencoder. In at least some instances, the cluster-mapped image can beneficially be used to identify, within seconds, chemically similar areas within the sample even when the measured spectra have relatively low signal-to-noise-ratio values.
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Patent Agency Ranking
公开(公告)号：US11861817B2
公开(公告)日：2024-01-02
申请号：US17235117
申请日：2021-04-20
Applicant: FEI Company
Inventor： Remco Schoenmakers , Maurice Peemen , Pavel Poto{hacek over (c)}ek
CPC classification number: G06T7/0002 , G06V20/693 , H01J37/28 , G06T2207/10061 , G06T2207/20084
Abstract: The invention relates to a method implemented by a data processing apparatus, comprising the steps of receiving an image; providing a set-point for a desired image quality parameter of said image; and processing said image using an image analysis technique for determining a current image quality parameter of said image. In the method, the current image quality parameter is compared with said desired set-point. Based on said comparison, a modified image is generated by using an image modification technique. The generating comprises the steps of improving said image in terms of said image quality parameter in case said current image quality parameter is lower than said set-point; and deteriorating said image in terms of said image quality parameter in case said current image quality parameter exceeds said set-point. The modified image is then output.
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公开(公告)号：US11488800B2
公开(公告)日：2022-11-01
申请号：US17214747
申请日：2021-03-26
Applicant: FEI Company
Inventor： Pavel Potocek , Remco Schoenmakers , Maurice Peemen , Bert Henning Freitag
IPC: H01J37/26 , H01J37/28 , G01N23/20 , H01J37/147 , G01N23/20091 , G01N23/2254 , G01N23/203 , H01J37/244
Abstract: Methods for drift corrected, fast, low dose, adaptive sample imaging with a charged particle microscopy system include scanning a surface region of a sample with a charged particle beam to obtain a first image of the surface region with a first detector modality, and then determining a scan strategy for the surface region. The scan strategy comprises a charged particle beam path, a first beam dwell time associated with at least one region of interest in the first image, the first beam dwell time being sufficient to obtain statistically significant data from a second detector modality, and at least a second beam dwell time associated with other regions of the first image, wherein the first beam dwell time is different than the second beam dwell time. The surface region of the sample is then scanned with the determined scan strategy to obtain data from the first and second detector.
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公开(公告)号：US20200272805A1
公开(公告)日：2020-08-27
申请号：US16287982
申请日：2019-02-27
Applicant: FEI Company
Inventor： John Flanagan , Erik Franken , Maurice Peemen
Abstract: Convolutional neural networks (CNNs) of a set of CNNs are evaluated using a test set of images (electron micrographs) associated with a selected particle type. A preferred CNN is selected based on the evaluation and used for processing electron micrographs of test samples. The test set of images can be obtained by manual selection or generated using a model of the selected particle type. Upon selection of images using the preferred CNN in processing additional electron micrographs, the selected images can be added to a training set or used as an additional training set to retrain the preferred CNN. In some examples, only selected layers of the preferred CNN are retrained. In other examples, two dimensional projections of based on particles of similar structure are used for CNN training or retraining.
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公开(公告)号：US20250006457A1
公开(公告)日：2025-01-02
申请号：US18345675
申请日：2023-06-30
Applicant: FEI Company
Inventor： Maurits Diephuis , Maurice Peemen , Hans Irma Stefaan Vanrompay , Narges Javaheri
IPC: H01J37/26
Abstract: Disclosed herein are scientific-instrument support systems, as well as related methods, apparatus, computing devices, and computer-readable media. In some embodiments, a support apparatus for a scientific instrument includes an interface device and a processing device. The interface device receives Ronchigrams acquired with the scientific instrument and transmits control signals for the electron-beam optics thereof. The processing device converts a measured Ronchigram into an input token for a transformer, produces an output token based on a tokenized sentence ending with the input token, and determines adjustments to the control signals based on the input and output tokens. The input and output tokens belong to a plurality of tokens representing reference Ronchigrams sampling an alignment parameter space of the electron-beam optics. The transformer implements an autoregressive masked language model trained on a corpus of reference sentences representing paths through the alignment parameter space to a target alignment state of the electron-beam optics.
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公开(公告)号：US20220373481A1
公开(公告)日：2022-11-24
申请号：US17329081
申请日：2021-05-24
Applicant: FEI Company
Inventor： Maurice Peemen , Holger Kohr , Pavel Potocek
IPC: G01N23/046 , G06T7/00 , G06T11/00 , G06T7/33
Abstract: Tomographic images are obtained by processing a tilt series of 2D images by aligning and combining images withing a group of neighbor images. The tilt series generally includes sparsely sampled images. Images of the tilt series at tilt angles associated with the sparsely sample images are selected as reference frames, grouped with neighbor images, and the group of images aligned. The aligned images are combined to produce replacement frames and a replacement frame tilt series that can be used for tomographic reconstruction.
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