Xu et al., 2025 - Google Patents
Machine learning-aided automatic recognition and precise localization of marker layers within multilayer Laue lenses (MLLs) for high-resolution X-ray nanofocusingXu et al., 2025
View HTML- Document ID
- 4100607633452171449
- Author
- Xu W
- Xu W
- Bouet N
- Zhou J
- Yan H
- Huang X
- Gao Z
- Lu M
- Chu Y
- Nazaretski E
- Publication year
- Publication venue
- Optics & Laser Technology
External Links
Snippet
We present a new method for the automatic recognition and precise localization of marker layers within multilayer Laue lenses (MLLs) used for high-resolution X-ray nanofocusing. This approach integrates image processing techniques with machine learning algorithms …
- 239000003550 marker 0 title abstract description 172
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation not covered by G01N21/00 or G01N22/00, e.g. X-rays or neutrons
- G01N23/22—Investigating or analysing materials by the use of wave or particle radiation not covered by G01N21/00 or G01N22/00, e.g. X-rays or neutrons by measuring secondary emission
- G01N23/225—Investigating or analysing materials by the use of wave or particle radiation not covered by G01N21/00 or G01N22/00, e.g. X-rays or neutrons by measuring secondary emission using electron or ion microprobe or incident electron or ion beam
- G01N23/2251—Investigating or analysing materials by the use of wave or particle radiation not covered by G01N21/00 or G01N22/00, e.g. X-rays or neutrons by measuring secondary emission using electron or ion microprobe or incident electron or ion beam with incident electron beam
- G01N23/2252—Investigating or analysing materials by the use of wave or particle radiation not covered by G01N21/00 or G01N22/00, e.g. X-rays or neutrons by measuring secondary emission using electron or ion microprobe or incident electron or ion beam with incident electron beam and measuring excited X-rays
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2223/00—Investigating materials by wave or particle radiation
- G01N2223/10—Different kinds of radiation or particles
- G01N2223/102—Different kinds of radiation or particles beta or electrons
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
- G01N15/10—Investigating individual particles
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN107077732B (en) | System and method for calculating focus changes for digital microscopes | |
US10462351B2 (en) | Fast auto-focus in imaging | |
EP2671113B1 (en) | Fast auto-focus in microscopic imaging | |
Yuan et al. | Training artificial neural networks for precision orientation and strain mapping using 4D electron diffraction datasets | |
DE112020002023T5 (en) | METHODS AND SYSTEMS FOR COMBINING X-RAY METROLOGY DATA SETS TO IMPROVE PARAMETER ESTIMATION | |
CN111542908B (en) | Charged particle beam device, computer readable recording medium | |
Zuidema et al. | Transmission imaging on a scintillator in a scanning electron microscope | |
Hua et al. | Learning to high-performance autofocus microscopy with laser illumination | |
Xu et al. | Machine learning-aided automatic recognition and precise localization of marker layers within multilayer Laue lenses (MLLs) for high-resolution X-ray nanofocusing | |
Kievits et al. | FAST-EM array tomography: a workflow for multibeam volume electron microscopy | |
CN115777060B (en) | Optical image contrast metric for optical target search | |
Kumagai et al. | Development of NMIJ CRM 5207-a tungsten dot-array for the image sharpness evaluation in scanning electron microscopy–structure evaluation and determination of dot-pitch | |
US8884223B2 (en) | Methods and apparatus for measurement of relative critical dimensions | |
Sun et al. | Deep learning model for 3D profiling of high-aspect-ratio features using high-voltage CD-SEM | |
Ledoux et al. | Gas-enhanced PFIB surface preparation enabled metrology and statistical analysis of 3D NAND devices | |
US12211295B2 (en) | Parallel image segmentation and spectral acquisition | |
Henderikx et al. | Ice thickness control and measurement in the VitroJet for time-efficient single particle structure determination | |
Shomrat et al. | Development and evaluation of three-dimensional metrology of nanopatterns using electron microscopy | |
Xu et al. | Machine learning-aided automatic and precise focal length estimation of multilayer Laue lenses for high-resolution hard x-ray microscopy | |
US20250165663A1 (en) | Methods and systems for obtaining a 3d profile of a sample | |
Osaki et al. | Quantification of three-dimensional pattern-shape variation with CD-SEM top-down image | |
Lin et al. | Unsupervised classification for region of interest in X-ray ptychography | |
Tang et al. | Segmentation and Classification of Fission as Pores in Reactor Irradiated Annular U–10Zr Metallic Fuel Using Machine Learning Models | |
Harris-Jones et al. | Applications of advanced metrology techniques for the characterization of extreme ultraviolet mask blank defects | |
Hakii et al. | Evaluation of 3D metrology potential using a multiple detector CDSEM |