A non-destructive inspection apparatus is provided. The non-destructive inspection apparatus includes at least one memory configured to store commands for performing predetermined operations, and at least one processor operatively coupled to the at least one memory and configured to execute the commands. The at least one processor is configured to obtain information on a transmission amount of an X-ray by emitting the X-ray to a part of a bicycle, generate a gray scale image based on the information on the transmission, measure an amount of change in a gray value from one end to the other end of the part of the bicycle represented in the gray scale image along an extending direction of the part, and detect an area in which the amount of change in the gray value is equal to or greater than a threshold, as an abnormal area.

A method of performing x-ray spectroscopy material analysis of a region of interest within a cross-section of a sample using an evaluation system that includes a focused ion beam (FIB) column, a scanning electron microscope (SEM) column, and an x-ray detector, including: forming a lamella having first and second opposing side surfaces in the sample by milling, with the FIB column, first and second trenches in the sample to expose the first and second sides surface of the lamella, respectively; depositing background material in the second trench, wherein the background material is selected such that the background material does not include any chemical elements that are expected to be within the region of interest of the sample; generating a charged particle beam with the SEM column and scanning the charged particle beam across a region of interest on the first side surface of the lamella such that the charged particle beam collides with the first side surface of the lamella at a non-vertical angle; and detecting x-rays generated while the region of interest is scanned by the charged particle beam.

A PET and Compton imaging method implemented by a device including at least two facing PET modules. The device includes a Compton camera arranged outside a plane containing the PET modules for forming a trihedron with the PET modules and producing a Compton view. The acquisition fields of the PET and Compton views having an overlap area covering the object to be imaged. The device allowing the following steps to be carried out: acquisition of a Compton view; location of a dense area and its contour on the Compton view; Computation of the 2D map of the probability of detection of the presence of a source from the Compton view of the Compton camera; Coincidence detection by the PET cameras and association of a response line (LOR); and Segmentation of LORs crossing the dense area by using the detection probability determined by the Compton view.

6Examples described herein provide a method that includes obtaining, by a processing device, three-dimensional (3D) voxel data. The method further includes performing, by the processing device, gray value thresholding based at least in part on the 3D voxel data and assigning a classification value to at least one voxel of the 3D voxel data. The method further includes defining, by the processing device, segments based on the classification value. The method further includes filtering, by the processing device, the segments based on the classification value. The method further includes evaluating, by the processing device, the segments to identify a surface voxel per segment. The method further includes determining, by the processing device, a position of a surface point within the surface voxel.

Scatter correction for tomography: for each position, two images are acquired, a first image without and a second image with a scatter reducing aperture plate (50). A scatter image is calculated by subtracting the second image from the first image. The apertures (48) in the scatter reducing plate (50) are arranged hexagonally in order to optimise the packaging density of the apertures.

To provide a charged particle beam image processing device in which a proper inspection region for an observation image that includes an edge of a line pattern can be set.

A charged particle beam image processing device performs image processing on an observation image generated by a charged particle beam apparatus, the charged particle beam image processing device includes: an extraction unit configured to extract an edge of a line pattern from an inspection region of the observation image; a division unit configured to divide the inspection region into sections each having a plurality of measurement points; a measurement unit configured to measure a line edge roughness in each of the sections and generate distribution data of the line edge roughness in each section; a calculation unit configured to calculate a line edge roughness in the entire inspection region and calculate a theoretical curve of the line edge roughness in each section; and a determination unit configured to determine whether the inspection region is proper based on a comparison between the distribution data and the theoretical curve.

A correction image acquisition process includes: a first gain image acquisition process of reading a pixel signal from a pixel region irradiated with radiation in a state in which a subject is not placed to acquire a first gain image; a pre-irradiation image acquisition process of reading the pixel signal from the pixel region in a state in which the subject is not placed and the radiation is not emitted to acquire a pre-irradiation image; a discarding process of discarding charge accumulated in a pixel of the pixel region after a dose of radiation that saturates the charge is emitted in a state in which the subject is not placed; a post-irradiation image acquisition process of reading the pixel signal from the pixel region to acquire a post-irradiation image after the discarding process is performed; and a second gain image acquisition process of subtracting the pre-irradiation image from the post-irradiation image to acquire a second gain image.

A method for analyzing at least one bounded object in an electron microscope image that includes segmenting the image to provide a segmented image and measuring a dimension relative to the at least one bounded object in the segmented image. The electron microscope image can be an image of a semiconductor device that includes a pattern of bounded objects or structure of the semiconductor device.

An example portable radiography scanning system includes: a radiation detector configured to generate a digital image based on incident radiation; a radiation emitter configured to output the radiation; a frame configured to hold at least one of the radiation emitter or the radiation detector such that the radiation emitter directs the radiation to the radiation detector; a first sensor configured to determine a first distance between the radiation detector and the radiation emitter; and a computing device configured to: determine a second distance between the radiation emitter and an interface between the radiation and the object; determine a magnification correction factor based on the first distance and the second distance; measure a size, in pixels, of a feature of the object in the digital image; and at least one of: calculate an actual size of the feature based on the magnification correction factor and the measured size of the feature, or determine whether the measured sized of the feature satisfies a threshold size based on the magnification correction factor.

In one embodiment, an X-ray inspection system may access a first set of X-ray images of one or more first samples that are labeled as being non-conforming. The system may adjust a classification algorithm based on the first set of X-ray images. The classification algorithm may classify samples into conforming or non-conforming categories based on an analysis of corresponding X-ray images. The system may analyze a second set of X-ray images of a number of second samples using the adjusted classification algorithm. The second samples may be previously inspected samples that have been classified as conforming by the classification algorithm during a previous analysis before the classification algorithm is adjusted. The system may identify one or more of the second samples from the second set of X-ray images. Each identified second sample may be classified as non-conforming by the adjusted classification algorithm.