A method is provided for image-processing an image dataset acquired from a patient by a medical imaging apparatus, (e.g., an X-ray apparatus), wherein the image dataset includes image values associated with image points, and depicts an acquisition region of the patient containing at least one object, (e.g., a medical device), to be enhanced, which is represented by image values within an image-value interval. The method includes determining a non-linearly high-pass filtered enhancement dataset, which is confined to an image portion containing image values lying in the image-value interval. The method also includes determining a result dataset by adding to the image dataset the enhancement dataset weighted by a weighting value. The method further includes outputting the result dataset.

The present invention relates to a pose estimation method of an interventional medical device using a single-view X-ray image which is captured using a bendable interventional medical device equipped with a plurality of radiopaque markers and using an X-ray source. The pose estimation method includes an operation (a) of defining a circle assuming that the interventional medical device is bent at a constant curvature, an operation (b) of extracting a position value of the marker from an X-ray image obtained by the X-ray source projecting X-rays onto the markers, and an operation (c) of setting a projection plane and estimating a shape of the circle using a position value of the marker extracted from a projected image obtained by perspective-projecting the circle onto the projection plane and using the position value of the marker extracted from the X-ray image.

A system and method for assessing an intravenous catheter site is described in embodiments herein. An application accessible on a mobile device may be used to take calibrated photographs of an intravenous catheter site. The resulting calibrated image may be compared to previously taken calibrated images to determine a complication. Success of treatments to the complication may be tracked and the patient's electronic medical record may be updated.

Embodiments disclosed herein provide systems, methods and/or computer-readable media for automatically detecting and removing fluorescence artifacts from catheter-based multimodality OCT-NIRAF images. In one embodiment, a process of determining an automatic threshold value (automatic thresholding) is implemented by sorting characteristic parameter values of the NIRAF signal and finding a maximum perpendicular distance between a curve of the sorted values and a straight line from the highest to the lowest sorted value, combined with the use of unsupervised machine learning classification techniques to detect the frame's NIRAF values that correspond to signal artifacts. Once the signal artifacts are detected, the system can filter out the signal artifacts, correct the frames that had artifacts, and produce a more accurate multimodality image.

A system and method for guiding invasive medical devices relative to other medical devices is disclosed. An imaging device can generate images of the invasive medical device within a body. A trained model for the invasive medical device can be trained on annotated images of the invasive medical device with at least one of orientation and position information. An imaging computer system can apply the trained model to unannotated images of the invasive medical device to determine at least one of a current orientation and a current position of the invasive medical device relative to another medical device within the body. At least one of visual orientation information representing the current orientation of the invasive medical device relative to the other medical device and visual position information representing the current position of the invasive medical device relative to the other medical device within the body can be outputted.

An image processing system is provided. The image processing system includes a display, a processor, and a memory. The memory stores processor-executable code that when executed by the processor causes receiving an image of a region of interest of a patient with a medical tube or line disposed within the region of interest, detecting the medical tube or line within the image, generating a combined image by superimposing a first graphical marker on the image that indicates an end of the medical tube or line, and displaying the combined image on the display.

An image analysis device is capable of outputting evaluation information for use in the balloon catheter treatment for subjects, in real time during a procedure using a balloon catheter. The image analysis device includes: an input unit configured to input captured image data of a two-dimensional captured image of a balloon catheter inserted into an organ of the subject and pressed against an inner surface of the organ; a processing unit configured to obtain evaluation image data of the two-dimensional evaluation image, by executing an image processing on the captured image based on the captured image data input by the input unit, and configured to obtain evaluation information regarding a state of the balloon catheter pressed against the inner surface of the organ based on the evaluation image data; and an output unit configured to output the evaluation information acquired by the processing unit.

An X-ray diagnosis apparatus according to an embodiment includes a processing circuitry. The processing circuitry is configured: to determine a region corresponding to a target object in an X-ray image, on the basis of the X-ray image; to calculate a statistical value related to the region, on the basis of a plurality of pixel values included in the region; and to set an X-ray condition related to generating X-rays, on the basis of the statistical value.

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 method for determining an abnormality in a medical device from a medical image is provided. The method for determining an abnormality in a medical device comprises receiving a medical image, and detecting information on at least a part of a target medical device included in the received medical image.