Computerized methods and systems for estimating a dual-energy X-ray absorptiometry (DEXA) score from CT imaging data by receiving imaging data of a computed tomography (CT) scan of a body of a patient containing at least a bone portion, segmenting the bone portion from the imaging data , computing at least one grade based on pixel associated values from the bone portion, and correlating the at least one grade with at least one score representing a relation to bone density values in a population obtained based on a DEXA scan. The grade is computed from a calculation of sub-grades performed for each one or a set of pixels having at least one of a common medial-lateral axial coordinate and a common cranial-caudal axial coordinate along a dorsal-ventral axis of a volume representation of the imaging data.

In at least one embodiment, X-ray images of a human examination object acquired via X-ray equipment are each spatially-resolved in a plurality of dimensions. In each case, one dimension extends in the head-foot direction of the examination object. The respective body region is detected in the X-ray images in steps that are equidistant in the head-foot direction and, based on this, the water-equivalent diameter of the examination object is determined in a plane orthogonal to the head-foot direction. The water equivalent diameters determined for each respective position is stored with allocation to the X-ray images and the respective position in the head-foot direction.

Disclosed is a method for management of geometric misalignment in an x-ray imaging system having an x-ray source, a photon-counting x-ray detector and an intermediate collimator structure in the x-ray path between the x-ray source and the x-ray detector. The x-ray detector includes a plurality of pixels, and the collimator structure includes a plurality of collimator cells, wherein each of at least a subset of the collimator cells corresponds to a NM matrix of pixels, where at least one of N and M is greater than one. The method includes monitoring, for a designated subset of pixels including at least two pixels that are affected differently by shadowing from the collimator structure due to geometric misalignment, output signals from the pixels of the designated subset, and determining the occurrence of geometric misalignment based on the monitored output signals from the pixels of the designated subset of pixels.

To that end, in order to overcome some of the deficiencies presented herein above, an exemplary system, method and computer-accessible medium for determining an attribute(s) of a brain of a patient, can include, for example, receiving information obtained from a computed tomography (CT) scan(s) of a portion(s) of the brain, generating a CT image(s) that can be based on the information, and determining the attribute(s) of the brain based on the CT image(s) by segmenting an intracranial space (ICS) in the CT image(s). The attribute(s) can include a presence or absence of Alzheimer's disease, total volume of the ICS, brain, CSF or a lesion or the volumes of ICS, brain, CSF or lesion(s) expressed as a percentage of other volume(s). The aforementioned areas can be segmented using a combination of thresholding, morphological erosions, morphological dilations, manual segmentation or semi-automatic segmentation techniques, all of which can be parallel procedures. These attributes can be further used to determine treatment, for example, optimizing the location of the twist drill craniotomy to drain hematoma in subdural hematoma.

One example method to improve image quality of projection image data may include obtaining projection image data and channel offset data associated with the projection image data. The channel offset data may be acquired using the flat panel detector and include at least one set of channel offset data values associated with respective channels of the flat panel detector. The method may also include generating channel offset drift data representing one or more variations of the channel offset data from a reference channel offset data. The method may further include generating offset-compensated projection image data by modifying the projection image data based on the channel offset drift data to compensate for the one or more variations of the channel offset data.

A method for correction of an x-ray image recorded with an x-ray device with an anti-scatter grid for effects of the anti-scatter grid is provided. The anti-scatter grid has a spatially periodically repeating geometrical embodiment, and a calibration image recorded without an imaging object is used. The calibration image and the x-ray image are transformed by a transformation into the position frequency space. In the position frequency space, adaptation parameters describing changes of the calibration image optimizing a measure of matching between the x-ray image and the calibration image are established. For correction, the adapted calibration image is subtracted from the x-ray image, and the x-ray image is transformed back into the position space again using an inverse of the transformation.

An X-ray imaging system (100) according to this invention includes an image processor (9) configured to generate a bone-suppressed tomographic image (20) representing a cross-section of a subject (101) in which a bone structure of a target part is suppressed based on a plurality of X-ray images (10). The image processor (9) includes a bone suppression processing unit (92) configured to suppress the bone structure of the target part, a reconstruction processing unit (93) configured to perform reconstruction for generating the tomographic image, and an adjustment processing unit (94) configured to adjust a suppression degree of the bone structure in the bone-suppressed tomographic image (20) to be generated.

A radiographic image capturing system includes the following. A capturing stand includes a holder to hold radiographic image capturing devices. A radiation irradiator is able to irradiate the radiographic image capturing devices at once. An image processor generates images based on image data acquired by the radiographic image capturing devices. The image processor removes a structural component derived from the front radiographic image capturing device, on the basis of a calibration image and the generated image. The calibration image is preliminarily generated based on the image data acquired by the rear radiographic image capturing device with no subject disposed. The generated image is generated based on the image data acquired by the rear radiographic image capturing device during actual image capturing. The image processor removes a streaky component residing in the generated image.

Various embodiments are described herein for methods, devices and systems that can be used to determine a breast density value from an input image of patient's breast. In one example embodiment, the breast density value is calculated by receiving an input image corresponding to the digital mammogram, removing metadata information from the input image to generate an intermediate image, generating a region of interest (ROI) image based on the intermediate image, extracting values for predictor variables based on the metadata information, the intermediate image and the ROI image, and calculating breast density based on the values of the predictor variables. The breast density value is calculated based on a breast density model.

Computerized methods and systems for estimating a dual-energy X-ray absorptiometry (DEXA) score from CT imaging data by receiving imaging data of a computed tomography (CT) scan of a body of a patient containing at least a bone portion, segmenting the bone portion from the imaging data, computing at least one grade based on pixel associated values from the bone portion, and correlating the at least one grade with at least one score representing a relation to bone density values in a population obtained based on a DEXA scan. The grade is computed from a calculation of sub-grades performed for each one or a set of pixels having at least one of a common medial-lateral axial coordinate and a common cranial-caudal axial coordinate along a dorsal-ventral axis of a volume representation of the imaging data.