Imaging systems and methods may facilitate positioning an imaging device in a procedure room. A 3D image of a subject may be obtained, where the subject is to have a procedure performed thereon. A view of the 3D image of the subject may be adjusted to a desired view and an associated 2D image reconstruction at the desired view may be obtained. A position for the imaging device that is associated with the desired view of the 3D image of the subject may be identified. Adjusting a view of the 3D image to a desired view and obtaining a 2D image reconstruction may be performed pre-procedure, such that a user may be able to create a list of desired views pre. A user may adjust a physical position of the imaging device to obtain reconstructed 2D preview images at the adjusted physical position of the imaging device prior to capturing an image.

A method and system for determining a PET image of the scan volume based on one or more PET sub-images is provided. The method may include determining a scan volume of a subject supported by a scan table; dividing the scan volume into one or more scan regions; for each scan region of the one or more scan regions, determining whether there is a physiological motion in the scan region; generating, based on a result of the determination, a PET sub-image of the scan region based on first PET data of the scan region acquired in a first mode or based, at least in part, on second PET data of the scan region acquired in a second mode; and generating a PET image of the scan volume based on one or more PET sub-images.

A method performed by a computing system comprises receiving a fluoroscopic image of a patient anatomy while a portion of a medical instrument is positioned within the patient anatomy. The fluoroscopic image has a fluoroscopic frame of reference. The portion has a sensed position in an anatomic model frame of reference. The method further comprises identifying the portion in the fluoroscopic image and identifying an extracted position of the portion in the fluoroscopic frame of reference using the identified portion in the fluoroscopic image. The method further comprises registering the fluoroscopic frame of reference to the anatomic model frame of reference based on the sensed position of the portion and the extracted position of the portion.

A medical navigation system including a controller configured to: generate a three-dimensional (3D) volume based upon acquired image information of a region of interest (ROI), determine a reference path (RP) to an object-of-interest (OOI) situated within the ROI, the RP defining an on-road path (ONP) through at least one natural pathway of an organ subject to cyclical motion and an adjacent off-road path (ORP) through tissue of the organ leading to the OOI, and an exit point situated between the ONP and the ORP, query an SSD within the at least one natural pathway to obtain SSDI, determine a shape and a pose of one or more portions of the SSD in accordance with the SSDI, calculate an error between the RP and the determined shape and pose of the SSD, and/or determine when or where to exit a wall of the natural pathway and begin the ORP based upon the calculated error.

Disclosed are an optimization method and system for a personalized contrast test based on deep learning, in which a contrast medium optimized for each individual patient is injected to implement optimum pharmacokinetic characteristics in a process of acquiring a medical image, the method including: obtaining drug information of a contrast medium and body information of a patient, in a contrast enhanced computed tomography (CT) scan; generating injection information of the drug to be injected into the patient by a predefined algorithm based on the drug information and the body information; injecting the drug into the patient based on the injection information, and acquiring a medical image by scanning the patient; and amplifying a contrast component in the medical image by inputting the medical image to a deep learning model trained in advance.

A method of treating a human patient identified as having an injury to a body region includes receiving CT images, where the CT images were generated by performing a CT angiography of an injured body region of the human patient. The method further includes determining, based on the CT images, a total volumetric rate of active bleeding in the injured body region; and recommending at least one treatment approach for the human patient based on the total volumetric rate of active bleeding.

Disclosed is an X-ray image processing apparatus including a data obtaining unit generating first to N-th images indicating an internal structure of an object and an image processing unit receiving the first to N-th images from the data obtaining unit, detecting a movement of the object, and generating a final image from the first to N-th images based on the movement of the object. The data obtaining unit actively controls an X-ray pulse irradiated based on the movement of the object.

A computer-implemented tumor position determining model is trained, based on a plurality of sets of image data, to determine a subsequent position of a tumor in a subject based on a subsequent 2D or 3D representation of a surface of the subject, an initial image of the tumor in the subject and an initial 2D or 3D representation of a surface of the subject. Each set of image data comprises an initial training image of a tumor in a subject, an initial training 2D or 3D representation of a surface of the subject, a subsequent training image of the tumor in the subject and a subsequent training 2D or 3D representation of a surface of the subject. The subsequent training image and the subsequent training 2D or 3D representation are taken at a subsequent point in time than the initial training image and the initial training 2D or 3D representation and the plurality of sets of image data are from a plurality of different subjects.

A method and breast imaging system for processing breast tissue image data includes feeding image data of breast images to an image processor, identifying image portions depicting breast tissue and high density elements and executing different processing methods on input images. A first image processing method involves breast tissue enhancement and high density element suppression, whereas the second image processing method involves enhancing high density elements. Respective three-dimensional sets of image slices may be generated by respective image processing methods, and respective two-dimensional synthesized images are generated and combined to form a two-dimensional composite synthesized image which is presented through a display of the breast imaging system. First and second image processing may be executed on generated three-dimensional image sets or two-dimensional projection images acquired by an image acquisition component at respective angles relative to the patient's breast.

A hybrid imaging system is disclosed including an arcuate arm defining a first and a second end the arcuate arm including a first detector assembly for 2D x-ray imaging of a patient and a second detector assembly for CT imaging of the patient, wherein the imaging system includes an internal drive mechanism for rotating the arcuate arm (e.g. translating the arcuate arm along an arcuate path) around the patient.