A radiography control apparatus includes a storage; a communicator that obtains irradiation information from an irradiation apparatus; and a hardware processor that: upon determining that the communicator obtains the irradiation information before a specific timing, executes image processing based on the irradiation information obtained from the communicator; and upon determining that the communicator does not obtain the irradiation information before the specific timing, executes the image processing based on information stored in advance in the storage.

The present disclosure is related to a method for scattering correction of an image. The method may include obtaining an image of a subject and a reference image of air. The method may also include identifying an OOI from the image, the OOI including one or more pixels. For each pixel of the one or more pixels of the OOI, the method may also include determining an equivalent thickness of the OOI corresponding to the each pixel based on a pixel value of the each pixel and the reference image, and determining a scatter correction coefficient of the each pixel based at least in part on the equivalent thickness of the OOI corresponding to the each pixel. The method may further include correcting the pixel value of the each pixel using the corresponding scatter correction coefficient for each pixel of the one or more pixels of the OOI.

The present disclosure is related to removing scatter from a SPECT scan by utilizing a radiative transfer equation (RTE) method. An attenuation map and emission map are acquired for generating scatter sources maps and scatter on detectors using the RTE method. The estimated scatter on detectors can be removed to produce an image of a SPECT scan with less scatter. Both first-order and multiple-order scatter can be estimated and removed. Additionally, scatter caused by multiple tracers can be determined and removed.

A method is provided to perform an imaging scan on a target tissue. The imaging scan includes generating a signal directed at a portion of a target tissue using a collimator that includes a slot, wherein a source of a signal assembly is incoherently interrupted. The method also includes receiving at least a portion of the signal from the portion of the target tissue at a linear signal detector positioned directly opposite from the signal assembly with respect to the target tissue, and simultaneously translating the linear signal detector and adjusting a width of the at least one slot of the collimator such that a fan width of the signal at the linear signal detector corresponds to a width of a detector window disposed in the linear signal detector. The method also includes rotating a stage about the target tissue, and repeating performing the imaging scan on the target tissue.

An X-ray imaging detector (102) is proposed, wherein the X-ray imaging detector comprises an X-ray converter (103) for converting X-ray radiation into electrical charges. The X-ray imaging detector further comprises a detector plate (104) for collecting the electrical charges generated by the X-ray converter and for generating an image. In addition, the X-ray imaging detector comprises a structured plate (105) for modulating the intensity of backscattered X-ray radiation, wherein the structured plate is arranged at a side of the detector plate opposite the side of the X-ray converter. Moreover, the X-ray imaging detector comprises a data processing system, which is configured for mitigating image distortions caused by backscattered X-ray radiation. Thereto, the data processing system uses information about the structured plate.

An improved x-ray cone-beam CT image reconstruction by end-to-end training of a multi-layered neural network is proposed, which employs cone-beam CT images of many patients as input training data, and precalculated scattering projection images of the same patients as output training data. After the training is completed, scattering projection images for a new patient are estimated by inputting a cone-beam CT image of the new patient into the trained multi-layered neural network. Subsequently, scatter-free projection images for the new patient are obtained by subtracting the estimated scattering projection images from measured projection images, beam angle by beam angle. A scatter-free cone-beam CT image is reconstructed from the scatter-free projection images.

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.

An image processing device (100) includes a noise reducer (22) including a pixel ratio acquirer (23) configured to acquire a pixel value ratio (α) between a scattered-ray reduced image (52) after reduction of a scattered-ray component and a radiation image (51) before the reduction of the scattered-ray component, the noise reducer being configured to reduce a noise component from the scattered-ray reduced image based on the pixel value ratio.

A fat mass derivation device includes at least one processor, in which the processor derives a fat mass distribution of a subject from a first radiation image and a second radiation image acquired by imaging the subject with radiation having different energy distributions, and derives a visceral fat mass distribution of the subject based on a shape of the fat mass distribution in a cross section orthogonal to a body axis of the subject.

Methods for quantitatively separating x-ray images of a subject having three or more component materials into component images using spectral imaging or multiple-energy imaging with 2D radiographic hardware implemented with scatter removal methods. The multiple-energy system may be extended by implementing DRC multiple energy decomposition and K-edge subtraction imaging methods.