An x-ray microscopy method that obtains a classification of different particles by distinguishing between different material phases through a combination of image processing involving morphological edge enhancement and possibly resolved absorption contrast differences between the phases along with optional wavelet filtering.

An image processing apparatus performs first noise reduction processing on a plurality of radiation images corresponding to mutually-different radiation energies, generates a decomposition image by energy subtraction processing using the plurality of radiation images obtained by performing the first noise reduction processing, and performs second noise reduction processing on the decomposition image, wherein the second noise reduction processing uses a filter that differs from a filter used in the first noise reduction processing in at least one of size and type.

Systems and methods for ascertaining a position of an orthopedic element in space comprising: capturing a first and second images of an orthopedic element in different reference frames using a radiographic imaging technique, detecting spatial data defining anatomical landmarks on or in the orthopedic element using a deep learning network, applying a mask to the orthopedic element defined by an anatomical landmark, projecting the spatial data from the first image and the second image to define volume data, applying the deep learning network to the volume data to generate a reconstructed three-dimensional model of the orthopedic element; and mapping the three-dimensional model of the orthopedic element to the spatial data to determine the position of the three-dimensional model of the orthopedic element in three-dimensional space.

A method comprising segmenting at least one vertebral body from at least one image of a first three-dimensional image data set. The method comprises receiving at least one image of a second three-dimensional image data set. The method comprises registering the segmented at least one vertebral body from the at least one image of the first three-dimensional image data set with the at least one image of the second three-dimensional image data set. The method comprises determining a position of the at least one surgical implant based on the at least one image of the second three-dimensional image data set and a three-dimensional geometric model of the at least one surgical implant. The method comprises overlaying a virtual representation of the at least one surgical implant on the registered and segmented at least one vertebral body from the at least one image of the first three-dimensional image data set.

An imaging device and a method for generating a motion-compensated image or video are provided. The imaging device has a data acquisition facility for acquiring image data of a target object. The imaging device is configured to acquire, using a registration facility, a posture of an inertial measurement unit and, on the basis thereof, to carry out a registration between coordinate systems of the inertial measurement unit and the image data. The imaging device is further configured to acquire motion data from the inertial measurement unit arranged on the target object and, by processing the motion data, to generate the motion-compensated image or video.

The present invention relates to a method for segmenting a digital image, for example to accurately segment cerebral vasculature on MRI-TOF images of a brain. The method first uses a model that imitates the perception of luminance contrasts by a human observer to accentuate a contrast between structures of interest, such as cerebral vasculature, and the image background. Then, the image is thresholded using an adaptive threshold. This enhanced segmentation method can be used to process digital images before launching further machine-implemented characterizations of the structures of interest, such as detecting and characterizing bifurcations of the cerebral vasculature for intra-cranial aneurysm prediction.

A method for generating a temporary image includes acquiring first data of an examination object, and providing at least one initialization image by applying a first processing function and/or a second processing function to the first data. The first processing function and the second processing function are at least partially different. The at least one initialization image is visualized. Further data of the examination object is acquired. Result data is provided by applying the first processing function to the further data. A result image is provided by applying the second processing function to the further data and/or the result data. The result data is provided before the result image. The temporary image is generated based on the result data and the at least one initialization image. The temporary image is visualized, and the result image is visualized.

Various methods and systems are provided for x-ray imaging. In one embodiment, a method includes acquiring a plurality of fluoroscopic images depicting an interventional tool positioned relative to an anatomy of interest of a patient, segmenting the interventional tool in the plurality of fluoroscopic images, measuring motion of the patient in the plurality of fluoroscopic images, correcting the plurality of fluoroscopic images to remove the motion of the patient, registering the segmented interventional tool to the anatomy of interest in the corrected plurality of fluoroscopic images, and displaying images with the segmented interventional tool registered to the anatomy of interest. In this way, a practitioner may view the position and movement of an interventional tool located within a patient relative to static images of the anatomy without motion artifacts or errors induced by patient motion such as respiratory motion or cardiac motion.

A marker-coordinate detecting unit detects coordinates of a stent marker on a new image when the new image is stored in an image-data storage unit; and then a correction-image creating unit creates a correction image from the new image through, for example, image transformation processing, so as to match up the detected coordinates with reference coordinates that are coordinates of the stent marker already detected by the marker-coordinate detecting unit in a first frame. An image post-processing unit then creates an image for display by performing post-processing on the correction image created by the correction-image creating unit, the post-processing including high-frequency noise reduction filtering-processing, low-frequency component removal filtering-processing, and logarithmic-image creating processing; and then a system control unit performs control of displaying a moving image of an enlarged image of a set region that is set in the image for display, together with an original image.

In one embodiment, a medical image processing apparatus includes: processing circuitry configured to extract 3D blood vessel data of an object from 3D image data of the object, detect a tip position of a medical device moving in a blood vessel in real time from a fluoroscopic image of the object inputted during an operation, and calculate at least one of a recommended route and a recommended direction of the medical device from the 3D blood vessel data, a rough route of the medical device, and the tip position of the medical device; and a terminal device configured to display a 3D blood vessel image of the object generated from the 3D blood vessel data and to designate the rough route of the medical device on the 3D blood vessel image.