A medical image-processing apparatus according to an embodiment includes processing circuitry configured to determine a position of a feature point of a device in a first X-ray image, and generate a superimposed image in which a 3D model expressing the device is superimposed on the first X-ray image or a second X-ray image that is acquired later than the first X-ray image. The processing circuitry is configured to superimpose the 3D model on the first X-ray image or the second X-ray image at a position based on the position of the feature point.

The present invention relates to an apparatus (10) for determining an orientation of a patients chest. The apparatus comprises: an input unit (20); and a processing unit (30). The input unit is configured to receive an image of a patient, the image comprising image data of the patients chest. The input unit is configured to receive an X-ray radiograph of the patient's chest acquired by an X-ray imaging unit with an X-ray imaging axis extending from an X-ray source to an X-ray detector. The input unit is configured to provide the image and the X-ray radiograph to the processing unit. The processing unit is configured to determine an orientation of the patients chest in the X-ray radiograph with respect to the X-ray imaging axis, the determination comprising utilization of the image and the X-ray radiograph.

A radiographing control apparatus includes a hardware processor. A radiographic imaging apparatus is exposed to a radiation from an irradiating apparatus through the subject. The hardware processor retrieves pre-exposure image data which the radiographic imaging apparatus generates by performing a pre-exposure to the subject at a pre-exposure dose of less than a dose of a subsequent main exposure, and calculates a total dose required to obtain diagnostic image data to be used for diagnosis. The hardware processor outputs a main exposure dose based on the calculated total dose to the irradiating apparatus and the radiographic imaging apparatus. The hardware processor retrieves main exposure image data which the radiographic imaging apparatus generates by performing the main exposure to the subject at the main exposure dose, and combines the main exposure image data with the pre-exposure image data to generate the diagnostic image data.

A method for processing breast tissue image data includes processing image data of a patient's breast tissue to generate a high-dimensional grid depicting one or more high-dimensional objects in the patient's breast tissue; determining a probability or confidence of each of the one or more high-dimensional objects depicted in the high-dimensional grid; and modifying one or more aspects of at least one of the one or more high-dimensional objects based at least in part on its respective determined probability or confidence to thereby generate a lower-dimensional format version of the one or more high-dimensional objects. The method may further include displaying the lower-dimensional format version of the one or more high-dimensional objects in a synthesized image of the patient's breast tissue.

The disclosure discloses a method, a device, a system and a computer storage medium for obtaining the CT perfusion imaging parameter maps of brain. The method includes: obtaining CT perfusion images, pre-processing the CT perfusion images, and obtaining discrete contrast agent concentration curves C(n) of each pixel point in the brain tissue; reading the acquisition time information of the CT perfusion images to obtain the acquisition time arrays T(n); intercepting the acquisition time arrays T(n) to obtain the relative acquisition time arrays t(n); combining the discrete contrast agent concentration curves C(n) with the corresponding relative acquisition time arrays t(n) to obtain the discrete time-concentration curves C(t.sub.n) of each pixel point in the brain tissue; after fitting or interpolating the discrete time-concentration curves C(t.sub.n), re-discretizing at the same time interval, and obtaining the discrete time-concentration curves C(n)′ of each pixel point in brain tissue.

For decision support in a medical therapy, machine learning provides a machine-learned generator for generating a prediction of outcome for therapy personalized to a patient. The outcome prediction may be used to determine dose. To assist in decision support, a regression analysis of the cohort used for machine training relates the outcome from the machine-learned generator to the dose and an actual control time (e.g., time-to-event). The dose that minimizes side effects while minimizing risk of failure to a time for any given patient is determined from the outcome for that patient and a calibration from the regression analysis.

X-ray devices and systems are described in this application. In particular, this application describes x-ray devices and systems that are used for three-dimensional (3D) image reconstruction with uncertain geometry. The x-ray imaging system contains an arm configured to be moved around an object to be imaged, a light weight, low power x-ray source attached to the arm, an x-ray detector configured to move complimentary to the x-ray source to capture multiple two-dimensional (2D) images in a solid angle path outside of a planar arc, 3D position and orientation tracking devices configured to capture the geometric position and orientation of the x-ray source and detector when each 2D projection image is captured, and a processor configured to construct a three dimensional (3D) image from the multiple 2D images using a reconstruction algorithm. These x-ray systems are lighter, more maneuverable, and less expensive than convectional CT x-ray systems because the geometry tracking devices combined with the processor and algorithm enable e generation of 3D images without the complex, precise, heavy, and expensive mechanical system that fixes the precise geometry of each 2D projection image to a high degree of accuracy. Other embodiments are described.

A method of detecting a protrusion in an intestinal tract in a computer according to an embodiment of the present disclosure includes acquiring a three-dimensional model of the intestinal tract scanned by a scanning device, the three-dimensional model comprising three-dimensional data of the intestinal tract; mapping, in the computer, the three-dimensional model to a two-dimensional plane in an area-preserving manner; and detecting an area of the protrusion in the two-dimensional plane. The method can replace traditional modes such as enteroscopy, and the protrusion in the intestinal tract is detected in a painless and low-cost mode.

The present disclosure is related to systems and methods for reconstructing a positron emission tomography (PET) image. The method includes obtaining PET data of a subject. The PET data may correspond to a plurality of voxels in a reconstructed image domain. The method includes obtaining a motion signal of the subject. The method includes obtaining motion amplitude data. The motion amplitude data may indicate a motion range for each voxel of the plurality of voxels. The method includes determining gating data based at least in part on the motion amplitude data. The gating data may include useful percentage counts each of which corresponds to at least one voxel of the plurality of voxels. The method includes gating the PET data based on the gating data and the motion signal. The method includes reconstructing a PET image of the subject based on the gated PET data.

Provided in the invention is a method and a device of Correction of a ring artifact in a CT image and a computer program medium. The method of correction comprises: pre-processing original detection data; marking a bad detector according to data in the pre-processed original sinogram; acquiring a replacing detection value corresponding to the bad detector by means of a first averaging processing; and performing a CT image reconstruction using a sinogram data after the first averaging processing. The device comprises: a pre-processing unit configured to pre-process original detection data; a marking unit configured to mark a bad detector according to data in the pre-processed original sinogram; a first averaging processing unit configured to acquire a replacing detection value corresponding to the bad detector by means of a first averaging processing; and an image reconstruction unit. The invention is able to effectively eliminate the ring artifact in the CT image, and at the same time ensure that there is little loss of the spatial resolution of the CT image.