A radiation imaging system includes a radiation imaging apparatus and an imaging control apparatus, the radiation imaging apparatus includes a dose detection pixel that detects a dose of radiation irradiated from a radiation source, and the imaging control apparatus controls the radiation imaging apparatus. Before radiation imaging, the imaging control apparatus specifies a position of the dose detection pixel in a region of interest for calculating a dose indicator value of a radiation image, determines a threshold according to the position of the dose detection pixel, and transmits the position of the dose detection pixel and the threshold to the radiation imaging apparatus. The radiation imaging apparatus makes a setting of the position of the dose detection pixel in the region of interest and the threshold transmitted from the imaging control apparatus, and performs imaging based on the setting.

An apparatus includes an acquisition unit and a display control unit. The acquisition unit is configured to acquire information about an orientation of a detector. The detector is configured to capture a radiation image by detecting radiation, and includes a plurality of receptor fields for performing automatic exposure control and a mark enabling identification of the orientation of the detector. The display control unit is configured to display an icon related to the detector on a display unit based on the acquired information about the orientation of the detector.

Gamma cameras may be used to obtain two-dimensional images of an emitting object, of which the most common form is the “Anger-type” gamma camera. The primary components in a conventional Anger-type gamma camera include, but are not limited to: a plurality of photo-multiplier tubes, a scintillator material, and a collimator. The disclosed invention claims a novel use of a gamma camera which eliminates the collimator. The new method is a method of forming an initial image from the incident radiation, which does not depend on any mechanical or other means of restricting the incident radiation to be passed on to a position-sensitive radiation detector. This method then uses mathematical deconvolution to produce an image of the object without the need for a collimator and without reliance on a pre-existing image.

An imaging planning apparatus according to one embodiment includes processing circuitry. The processing circuitry obtains a first value of a first index that is related to an X-ray dose and a second value of a second index that is related to an image quality, based on an X-ray imaging condition of a subject set in a predetermined examination. The processing circuitry displays an association chart indicating an association between the first index and the second index on a display unit, displays an acceptable range of the first index and the second index, the acceptable range being based on information related to a diagnostic reference level corresponding to the predetermined examination, in a manner distinguished from a range other than the acceptable range in the association chart, and also displays a mark at a position corresponding to the first value and the second value in the association chart.

The present disclosure relates to a method for scanning a patient in an imaging system. The imaging system may include one or more cameras directed at the patient. The method may include obtaining a position of each of the camera(s) relative to the imaging system. The method may also include obtain image data of the patient captured by the camera(s), wherein the image data may correspond to a first view with respect to the patient. The method may further include generating projection image data of the patient based on the image data and the position of each of the camera(s) relative to the imaging system, wherein the projection image data may correspond to a second view with respect to the patient different from the first view. The method may further include generating control information for scanning the patient based on the projection image data of the patient.

A 3-D convolutional autoencoder for low-dose CT via transfer learning from a 2-D trained network is described, A machine learning method for low dose computed tomography (LDCT) image correction is provided. The method includes training, by a training circuitry, a neural network (NN) based, at least in part, on two-dimensional (2-D) training data. The 2-D training data includes a plurality of 2-D training image pairs. Each 2-D image pair includes one training input image and one corresponding target output image. The training includes adjusting at least one of a plurality of 2-D weights based, at least in part, on an objective function. The method further includes refining, by the training circuitry, the NN based, at least in part, on three-dimensional (3-D) training data. The 3-D training data includes a plurality of 3-D training image pairs. Each 3-D training image pair includes a plurality of adjacent 2-D training input images and at least one corresponding target output image. The refining includes adjusting at least one of a plurality of 3-D weights based, at least in part, on the plurality of 2-D weights and based, at least in part, on the objective function. The plurality of 2-D weights includes the at least one adjusted 2-D weight.

A computer-implemented method is provided for improving live video quality. The method comprises: acquiring, using a medical imaging apparatus, a stream of consecutive image frames of a subject, and the stream of consecutive image frames are acquired with reduced amount of radiation dose; applying a deep learning network model to the stream of consecutive image frames to generate an image frame with improved quality; and displaying the image frame with improved quality in real-time on a display.

An x-ray system and method can improve speed of imaging and/or reduce radiation dosage compared to conventional imaging technique, such as CT. The system can identify a volume of interest within a subject. The system can include scatter removal algorithms and/or a beam selection device. Material decomposition of the imaged subject can be based on the dual energy decomposition method which can be iterative to solve the energy response function equation system. X-rayx-rayx-rayx-rayx-rayX-rayX-rayX-ray

A radiation imaging control apparatus is provided that includes a camera imaging control unit configured to control a camera apparatus to image an implementation state of a radiation imaging examination, a subject body shape recognition unit configured to recognize a body shape in an imaging part of a subject by using a camera image imaged by the camera apparatus under a control of the camera imaging control unit, a specifying unit configured to specify a radiation imaging setting related to the radiation imaging examination by using the body shape in the imaging part of the subject recognized by the subject body shape recognition unit, and a selecting unit configured to select the radiation imaging setting specified by the specifying unit as setup information of the radiation imaging examination.

In a multi-session imaging study, information from a previous imaging session is stored in a Binary Large Object (BLOB). Current emission imaging data are reconstructed into a non-attenuation corrected (NAC) current emission image. A spatial transform is generated aligning a previous NAC emission image from the BLOB to the current NAC emission image. A previous computed tomography (CT) image from the BLOB is warped using the spatial transform, and the current emission imaging data are reconstructed with attenuation correction using the warped CT image. Alternatively, low dose current emission imaging data and a current CT image are acquired, a spatial transform is generated aligning the previous CT image to the current CT image, a previous attenuation corrected (AC) emission image from the BLOB is warped using the spatial transform, and the current emission imaging data are reconstructed using the current CT image with the warped AC emission image as prior.