A method for providing a prognosis data record includes receiving a first image data record relating to an examination region of an examination object, and receiving an operating parameter of a medical object that is arranged at the examination region of the examination object and positioning information of the medical object that is arranged at the examination region. The prognosis data record is created by applying a trained function to input data. The input data is based on the first image data record, the at least one operating parameter, and the positioning information of the medical object. At least one parameter of the trained function is based on a comparison with a first comparison image data record. As compared with the first image data record, the first comparison image data record includes changes influenced by the medical object at the examination region. The prognosis data record is provided.

A system may transform sensor data from a sensor domain to an image domain using data-driven manifold learning techniques which may, for example, be implemented using neural networks. The sensor data may be generated by an image sensor, which may be part of an imaging system. Fully connected layers of a neural network in the system may be applied to the sensor data to apply an activation function to the sensor data. The activation function may be a hyperbolic tangent activation function. Convolutional layers may then be applied that convolve the output of the fully connected layers for high level feature extraction. An output layer may be applied to the output of the convolutional layers to deconvolve the output and produce image data in the image domain.

A system and method is provided for magnetic resonance imaging (MRI) guided respiratory gated radiotherapy using a respiratory motion model. MRI-guided respiratory gating is performed with a continuously updated model that represents a patient's internal anatomy as a mathematical function of an external respiratory surrogate. The motion model may be built and updated by acquiring images of a tissue in a subject and measuring, using the images, a position of the tissue in the images to determine motion of the tissue. The surrogate respiratory signal is acquired contemporaneously with acquiring the images. Motion of the tissue and the surrogate respiratory signal are correlated to create the motion model for the subject and gating a radiotherapy system may then be based upon the motion model. A multi-planar model-based respiratory gating may also be performed by sequentially imaging a stack of adjacent slice positions.

Systems and methods for obtaining simultaneous X-ray—magnetic resonance imaging (MRI) images are provided. A magnetic resonance X-ray CT (MRX) system can combine X-ray imaging and MRI in a cost-effective and relatively simple solution for improved imaging. During imaging of a subject, the X-ray source and X-ray detector can be simultaneously rotated around the subject, and the means for generating a magnetic field can also be rotated around the subject. The means for generating a magnetic field can be a plurality of permanent magnets.

A method for postural independent location of targets in diagnostic images acquired by multimodal acquisitions, compensating for deformation of soft tissues due to changing posture, includes generating a transition of a digital image of the inside of a target region from a first to a second position by correlating the position of markers placed on the external surface of the target region in a digital image of the inside of the target region and in a digital representation of the external surface of the target region acquired by optically scanning the external surface; and at a later time registering the diagnostic image of the inside of the target region, transitioned into the second position, with a diagnostic image of the same target region acquired with the target region in the second position by matching a second representation of the external surface of the target region in the second position without markers with the diagnostic image of the inside of the target region transitioned into the second position.

Systems and methods for improving soft tissue contrast, characterizing tissue, classifying phenotype, stratifying risk, and performing multi-scale modeling aided by multiple energy or contrast excitation and evaluation are provided. The systems and methods can include single and multi-phase acquisitions and broad and local spectrum imaging to assess atherosclerotic plaque tissues in the vessel wall and perivascular space.

Method and/or apparatus embodiments for 3-D cephalometric analysis of a patient according to the application can display reconstructed volume image data from a computed tomographic scan of a patient's head including segmented dentition elements having an initial arrangement from one or more 2D/3D views; can compute and display a plurality of cephalometric parameters for the patient according to the reconstructed volume image data; then use the patient specific cephalometric parameters and population biometry data, to identify one or more maxillofacial/dental abnormalities; and compose patient specific treatment plans to correct selected dentition abnormalities using maxillofacial/dental structure, which can be composed in a final tooth arrangement in a final virtual CT volume. One or more aligners can be generated to incrementally move dentition from the initial arrangement to the final tooth arrangement.

The present invention relates to navigating in bronchial pathways. In order to provide further improved navigation guidance, a sequence of 2D X-ray images of a region of interest of a bronchial structure with an intrathoracic device (visible in the X-ray images) inserted in a bronchial pathway is provided. The intrathoracic device is tracked in the 2D X- ray images and direction and magnitude of repetitory cardiovascular and respiratory induced motion is assessed based on the tracked intrathoracic device. The assessed motion is modelled and a navigation information indicative of a range of the modelled motion is generated. The navigation information is shown as a confidence reference (310), for example a rEBUS historical trajectory confidence reference, to a user operating the intrathoracic device. As an example, an augmented fluoroscopy 2D image (302) of a thorax region is registered and shown overlaid with segmentation (304) of the bronchial structure and target lesion (312). Further, a confidence reference (314) of the current position of the rEBUS catheter may also be shown.

A system comprises an image capture device, an augmented reality (AR) display to display, and a processing device. The processing deice receives image data of a dental arch from the image capture device and processes the image data using a plurality of detection rules, where each detection rule detects one or more dental conditions. The processing device determines a dental condition for the dental arch based on the processing, determines a position of an area of interest on the dental arch, wherein the area of interest is associated with the dental condition, generates a visual overlay comprising an indication of the dental condition at the position of the area of interest, and outputs the visual overlay to the AR display, wherein the visual overlay is superimposed over a view of the dental arch on the AR display at the position of the area of interest.

The present disclosure provides a system and method for medical imaging. The method may include obtaining a preliminary image and scanning data of a subject acquired using a scanner. The method may also include determining a regularization parameter for a regularization item of an objective function based at least in part on the scanning data, wherein the regularization parameter includes at least two of a first component characterizing quality of the scanning data, a second component characterizing the scanner, or a third component characterizing a feature of the subject. The method may further include generating an image of the subject by reconstructing the preliminary image based on the objective function.