Fei Comapny

Other

Fbi Company

Remco Schoenmakers

Pavel Potocek

Maurice Peemen

Faysal Boughorbel

Uwe Luecken

Bert Henning Freitag

Erik Michiel Franken

Peter Christiaan Tiemeijer

Frank Jeroen Pieter Schuurmans

Bart Jozef Janssen

Yuchen Deng

Holger Kohr

Ondrej Machek

Johannes Antonius Maria Van Den Oetelaar

Oleksii Kaplenko

David Foord

Jaydeep Sanjay Belapure

Martin Verheijen

Mykola Kaplenko

Andreas Voigt

Pavel Potoček

Franciscus Martinus Henricus Maria Van Laarhoven

Maurice Peeman

Johannes Van Den Oetelaar

Pavel Poto Ek

Erik Franken

Frank Van Laarhoven

Frank Schuurmans

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 a step of 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 and may be further analysed.

Method implemented by a data processing apparatus, and charged particle beam device for inspecting a specimen using such a method

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.

Dual speed acquisition for drift corrected, fast, low dose, adaptive compositional charged particle imaging

The disclosure relates to a method of aligning a charged particle beam apparatus, comprising the steps of providing a charged particle beam apparatus in a first alignment state; using an alignment algorithm, by a processing unit, for effecting an alignment transition from said first alignment state towards a second alignment state of said charged particle beam apparatus; and providing data related to said alignment transition to a modification algorithm for modifying said alignment algorithm in order to effect a modified alignment transition.

Method of aligning a charged particle beam apparatus

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.

The present invention relates to a method of training a network for reconstructing and/or segmenting microscopic images comprising the step of training the network in the cloud. Further, for training the network in the cloud training data comprising microscopic images can be uploaded into the cloud and a network is trained by the microscopic images. Moreover, for training the network the network can be benchmarked after the reconstructing and/or segmenting of the microscopic images. Wherein for benchmarking the network the quality of the image(s) having undergone the reconstructing and/or segmenting by the network can be compared with the quality of the image(s) having undergone reconstructing and/or segmenting by already known algorithm and/or a second network.

Method, device and system for remote deep learning for microscopic image reconstruction and segmentation

The invention relates to a method of examining a sample using a charged particle microscope, comprising the steps of providing a charged particle beam, as well as a sample; scanning said charged particle beam over said sample at a plurality of sample positions; and acquiring an EELS spectrum for each of said plurality of sample positions. According to the method, it comprises the further steps of scanning, once more, said charged particle beam over said sample at said plurality of sample positions; acquiring a further EELS spectrum for each of said plurality of sample positions; and combining, for each of said plurality of sample positions, said EELS spectrum with said further EELS spectrum. With this, it is possible to acquire rapid information on the sample being investigated, allowing for faster processing of samples.

Method of examining a sample using a charged particle microscope, wherein an electron energy-loss spectroscopy (EELS) spectrum is acquired

Methods and systems for neural network based image restoration are disclosed herein. An example method at least includes acquiring a plurality of training image pairs of a sample, where each training image of each of the plurality of training image pairs are images of a same location of a sample, and where each image of the plurality of training image pairs are acquired using same acquisition parameters, updating an artificial neural network based on the plurality of training image pairs, and denoising a plurality of sample images using the updated artificial neural network, where the plurality of sample images are acquired using the same acquisition parameters as used to acquire the plurality of training image pairs.

Acquisition strategy for neural network based image restoration

The invention relates to a method of imaging a sample, said sample mounted on a sample holder in an electron microscope, the electron microscope comprising an electron source for generating a beam of energetic electrons along an optical axis and optical elements for focusing and deflecting the beam so as to irradiate the sample with a beam of electrons. The sample holder is capable of positioning and tilting the sample with respect to the electron beam. The method comprises the step of acquiring a tilt series of images by irradiating the sample with the beam of electrons, and concurrently changing a position of the sample during acquisition of the images, so that each image is acquired at an associated unique tilt angle and an associated unique position.

Method of imaging a sample using an electron microscope

Methods of investigating a specimen using tomographic imaging include directing a beam of radiation through a specimen and onto a detector, thereby generating an image of the specimen. The directing is repeated for different specimen orientations relative to the beam, thereby generating a corresponding set of images. An iterative mathematical reconstruction technique is used to convert the images into a tomogram. The reconstruction is mathematically constrained to curtail a solution space using three-dimensional SEM imagery of at least a part of the specimen that overlaps the tomogram by requiring iterative results of the reconstruction to be consistent with pixel values derived from the SEM imagery.

Tomographic imaging method

Systems and methods for controlling an imaging device are disclosed. In one aspect, a method determines a set of control parameters for the imaging device, and acquires an image based on the set of control parameters. The method determines a plurality of image quality measurements of the first image. A polygon may be displayed on an electronic display based on a plurality of image quality measurements. For example, positions of polygon vertices may be determined relative to an origin point based on corresponding image quality measurements. In some aspects, input may be received from a user interface indicating a change in position of one or more of the vertices and the corresponding image quality measurements. In some aspects, a new set of control parameters may then be determined to achieve the changed image quality measurement(s). In some aspects a composite measure of the image quality measurements may also be displayed.

Interactive graphical representation of image quality and control thereof

A Charged Particle Microscope includes The illuminator includes: The aperture region includes a distribution of multiple holes, each of which is smaller than a diameter of the beam incident on the aperture plate.

Charged particle microscope with special aperture plate

The invention relates to a method of performing tomographic imaging involving repeatedly directing a charged particle beam through a sample for a series of sample tilts to acquire a corresponding set of images and mathematically combining the images to construct a composite image. The latter of which consists of, at each of a second series of sample tilts, using a spectral detector to accrue a spectral map of said sample, thus acquiring a collection of spectral maps; analyzing said spectral maps to derive compositional data of the sample; and employing said compositional data in constructing said composite image.

Method of performing tomographic imaging of a sample in a charged-particle microscope

The invention relates to an improved method of electron tomography. Electron tomography is a time consuming process, as a large number of images, typically between 50-100 images, must be acquired to form one tomogram. The invention teaches a method to shorten the time needed to acquire this amount images much more quickly by tilting the sample continuously, instead of step-by-step. Hereby the time needed to reduce vibrations between steps is eliminated.

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Remco Schoenmakers