The radiographic system including a plurality of radiation detection apparatuses, which detect radial rays, a combining processor which generates a long-size image by combining a plurality of radiation images obtained from the radiation detection apparatuses, and an image correction unit, which corrects a defective region in which the plurality of radiation detection apparatuses overlap with each other in the long-size image.

Iterative material decomposition of multispectral image data includes providing a plurality of spectral images of a region of interest comprising a body part and a plurality of sets of material coefficients for a plurality of materials. Each spectral image is decomposed into a plurality of material images and an offset image. At least one of the material images for each spectral image is manipulated on the basis of at least one topological constraint relating to the body part to determine for each spectral image an updated plurality of material images and an updated offset image. A plurality of spectral images is then recomposed from the corresponding updated plurality of material images and the updated offset. Intensities at image locations are compared, and the updated plurality of material images is modified. The steps are repeated until convergence, and at least one of the recomposed spectral images at convergence is output.

A deep-learning-based method for metal artifact reduction in CT images includes providing a dataset and a cGAN. The dataset includes CT image pairs, randomly partitioned into a training set, a validation set, and a testing set. Each Pre-CT and Post-CT image pairs is respectively acquired in a region before and after an implant is implanted. The Pre-CT and Post-CT images of each pair are artifact-free CT and artifact-affected CT images, respectively. The cGAN is conditioned on the Post-CT images, includes a generator and a discriminator that operably compete with each other, and is characterized with a training objective that is a sum of an adversarial loss and a reconstruction loss. The method also includes training the cGAN with the dataset; inputting the post-operatively acquired CT image to the trained cGAN; and generating an artifact-corrected image by the trained cGAN, where metal artifacts are removed in the artifact-corrected image.

An optical waveguide-transmitter apparatus, an ultrasonic transceiver apparatus, an ultrasonic imaging apparatus and an associated production method are disclosed. The optical waveguide-transmitter apparatus includes a substrate made of a semiconductor material; a carrier layer arranged on the substrate; and at least one transmitter-optical waveguide made of a semiconductor material with a refractive index greater than a refractive index of the carrier layer. At least one side of the waveguide is at least partially surrounded by the carrier layer. The waveguide is configured at an end facing toward the examination region for a decoupling of the light beams into the examination region for generating the ultrasonic waves in the examination region by way of the decoupled light beams for an optoacoustic imaging and/or has, on the end facing toward the examination region, an optical absorption layer for such a conversion of the light beams.

This X-ray imaging apparatus includes an X-ray irradiation unit, an X-ray detection unit, an X-ray image generation unit, and a control unit. The control unit includes: an enhanced image generation unit for generating an enhanced image in which a foreign object included in the X-ray image has been enhanced; an identification image generation unit for generating an identification image for identifying the foreign object by coloring a portion corresponding to the enhanced foreign object based on the enhanced image; and an image output unit for outputting an identification image.

A system and method for generating a rib suppressed radiographic image using deep learning computation. The method includes using a convolutional neural network module trained with pairs of a chest x-ray image and its counterpart bone suppressed image. The bone suppressed image is obtained using a bone suppression algorithm applied to the chest x-ray image. The convolutional neural network module is then applied to a chest x-ray image or the bone suppressed image to generate an enhanced bone suppressed image.

In a case in which an imaging mode continuously acquiring a plurality of energy subtraction images is performed, a radiation source control unit of a control device performs radiation source control for performing a one-shot imaging operation, in which only one of first radiation and second radiation is emitted, at least once for one two-shot imaging operation in which the first radiation and the second radiation are continuously emitted. In a case in which the imaging mode is performed, a detector control unit performs detector control to direct a radiation detector to output a first radiographic image based on the first radiation and a second radiographic image based on the second radiation.

The present disclosure directs to a system and method for image processing. The method for image processing comprises acquiring a plurality of original computed tomography (CT) images of a spine of a subject; generating CT value images of the spine of the subject by processing the plurality of original CT images. The method further includes identifying an optimal sagittal image in which a centerline of the spine is located based on the CT value images. The method further includes identifying the centerline of the spine within the optimal sagittal image. The method further includes identifying a center point and a direction of at least one intervertebral disc along the centerline of the spine. The method still further includes reconstructing an image of the at least one intervertebral disc based on the center point and the direction of the at least one intervertebral disc.

A curved compression element, such as a breast compression paddle, and imaging systems and methods for use with curved compression elements. A system may include a radiation source, a detector, and a curved compression element. Operations are performed that include receiving image data from the detector; accessing a correction map for the at least one compression paddle; correcting the image data based on the correction map to generate a corrected image data; and generating an image of the breast based on the corrected image data. The breast compression element generally has no sharp edges, but rather has smooth edges and transitions between surfaces. The breast compression paddle also includes a flexible material that spans a portion of a curved bottom surface of the breast compression paddle to define a gap. The flexible material may be a thin-film material such as a shrink wrap.

An image acquisition unit acquires two radiographic images based on radiations which are transmitted through a subject containing a plurality of compositions and have energy distributions different from each other. A body thickness derivation unit derives, as a first body thickness and a second body thickness, body thicknesses of the subject for pixels of the two radiographic images. A composition ratio derivation unit derives composition ratios of the subject for the pixels of the radiographic images based on the first body thickness and the second body thickness.