An X-ray CT system includes an X-ray tube, an X-ray detector and processing circuitry. The processing circuitry is configured to cyclically change energy of the X-rays during one rotation of the X-ray tube around a subject. The processing circuitry is configured to perform a process including a correcting process addressing a difference in a transmission amount between X-rays having first energy and X-rays having second energy, on at least one selected from between: a plurality of first projection data sets acquired when the X-rays having the first energy were radiated; and a plurality of second projection data sets acquired when the X-rays having the second energy were radiated. The processing circuitry is configured to reconstruct an image on the basis of a combined data set generated on the basis of a plurality of projection data sets including the projection data sets resulting from the process.

A x-ray micro tomography system provides the ability to proscriptively determine regularization parameters for iterative reconstruction of a sample, from projection data of the sample. This allows a less experienced operator to determine the regularization parameters with adequate precision.

A method for detecting defects in a product (10), such as food packaging, having a range of thicknesses of cross-section through which detection will take place; the method comprising: scanning the product (10), with for instance x-rays, to identify one or more light regions, and one or more dense regions of the product; and creating a first signal path and a second signal path from a single set of scanning data, and conditioning: the first signal path for detection of defects in the one or more dense regions; and the second signal path for detection of defects (14a, 14b, 14c) in the one or more light regions. Advantageously, detection of defects in the contents (dense region) of a product and the seal (light region) of the product is conducted simultaneously.

An isosurface mesh M is generated by extracting voxels having a certain CT value from volume data obtained by X-ray CT. A gradient vector g of a CT value is calculated at each vertex p of the isosurface mesh M. A plurality of sample points S are generated in positive and negative directions of the calculated gradient vector g. Gradient norms N of CT values at the respective generated sample points S are calculated. The vertex p of the isosurface mesh is moved and corrected to a sample point Sm having the maximum norm Nm calculated.

Methods and systems for performing electron microscopy are provided. Microscopy images candidate sub-regions at different magnification levels are captured and provided to a trained sub-region quality assessment application trained to output a quality score for each candidate sub-region. From the quality scores, group-level features for the larger magnification images are determined using a group-level feature extraction application. The quality scores for the candidate sub-regions and the group-level extraction features are provided to a trained Q-learning network that identifies a next sub-region amongst the candidate sub-regions for capturing a micrograph image, where reinforcement learning may be used with the Q-learning network for such identification, for example using a decisional cost.

A system and method for identifying lithology based on images and XRF mineral inversion solving the problem that conventional lithology identification relies on manual work, which is time-consuming, subjective and can cause misjudgment. The identification system includes an autonomous vehicle; an X ray fluorescence spectrometer probe, and tests surrounding rock element information; image collection device; and vehicle-mounted processor. The processor inverts the received surrounding rock element information into mineral information based on a Barthes-Niggli standard mineral calculation method; and receive surrounding rock images and a corresponding inclination angle thereof, convert the surrounding rock images into image information in a one-dimensional vector format, splice the image and mineral information which is in a one-dimensional format, and distinguish the spliced information based on a preset neural network to identify rock lithology.

A x-ray micro tomography system provides the ability to proscriptively determine regularization parameters for iterative reconstruction of a sample, from projection data of the sample. This allows a less experienced operator to determine the regularization parameters with adequate precision.

An X-ray single-pixel camera based on X-ray computational correlated imaging, which belongs to the technical research fields of X-ray computational correlated imaging and X-ray single-pixel imaging. The X-ray single-pixel camera includes: an X-ray modulation system (3), an X-ray modulation control system (4), an X-ray single-pixel detector (5), a main control system unit (6), a time synchronization system (7) and a computational imaging system (8). The main control system unit (6) controls each module through software; the time synchronization system (7) controls synchronization of each module for automatic collection; and the computational imaging system (8) is configured to perform a second-order correlated computation or a compressed sensing computation or a deep learning computation on the signals collected by the X-ray single-pixel detector (5) and a preset modulation matrix, so as to obtain an image of an object under test. The X-ray single-pixel camera based on X-ray computational correlated imaging, provided by the present invention, realizes single-pixel imaging, greatly reduces the sampling number while ensuring the imaging quality, and reduces the X-ray radiation dose in an imaging process.

A x-ray micro tomography system provides the ability to proscriptively determine regularization parameters for iterative reconstruction of a sample, from projection data of the sample. This allows a less experienced operator to determine the regularization parameters with adequate precision.

The invention relates to a screening method. The method comprises the step of providing a sample, wherein said sample comprises a sample carrier with a surface structure, as well as an object of interest. The method further comprises the step of acquiring an image of said sample. According to the disclosure, the method comprises the steps of providing information on said surface structure of said sample carrier, which may in particular comprise the step of acquiring an image of said sample carrier. In that case two images are obtained: one more sensitive to the objects of interest, and one more sensitive to the surface structure of the sample carrier. This allows manipulation of the acquired image, using said information on the surface structure of the sample carrier. With this, said manipulated image may be screened for easy and reliable detection of said object of interest.