A method for automated detection of landmarks from 3D medical image data using deep learning according to the present inventive concept, the method includes receiving a 3D volume medical image, generating a 2D intensity value projection image based on the 3D volume medical image, automatically detecting an initial anatomical landmark using a first convolutional neural network based on the 2D intensity value projection image, generating a 3D volume area of interest based on the initial anatomical landmark and automatically detecting a detailed anatomical landmark using a second convolutional neural network different from the first convolutional neural network based on the 3D volume area of interest.

Methods are provided for dynamically visualizing information in image data of an object of interest of a patient, which include an offline phase and an online phase. In the offline phase, first image data of the object of interest acquired with a contrast agent is obtained with an interventional device is present in the first image data. The first image data is used to generate a plurality of roadmaps of the object of interest. A plurality of reference locations of the device in the first image data is determined, wherein the plurality of reference locations correspond to the plurality of roadmaps. In the online phase, live image data of the object of interest acquired without a contrast agent is obtained with the device present in the live image data, and a roadmap is selected from the plurality of roadmaps. A location of the device in the live image data is determined. The reference location of the device corresponding to the selected roadmap and the location of the device in the live image data is used to transform the selected roadmap to generate a dynamic roadmap of the object of interest. A visual representation of the dynamic roadmap is overlaid on the live image data for display. In embodiments, the first image data of the offline phase covers different of phases of the cardiac cycle of the patient, and the plurality of roadmaps generated in the offline phase covers the different phases of the patient's cardiac cycle. Related systems and program storage devices are also described and claimed.

A non-transitory computer-readable storage medium stores a control program that causes a computer to perform first frame displaying. In the first frame displaying, the computer displays thumbnails of a series of frames next to each other on a display, the series of frames constituting a dynamic image of a subject or constituting a dynamic analysis image obtained by analyzing the dynamic image.

A system and method for reviewing a tomosynthesis image data set comprising volumetric image data of a breast, the method comprising, in one embodiment, causing an image or a series of images from the data set to be displayed on a display monitor and selecting or indicating through a user interface an object or region of interest in a presently displayed image of the data set, thereby causing an image from the data set having a best focus measure of the user selected or indicated object or region of interest to be automatically displayed on the display monitor.

A system and method for generating reports on perfusion blood volume from computed tomography (CT) data acquired from a subject. The method includes receiving multi-faceted CT data acquired from the subject using one of a multi-energy or polychromatic CT acquisition and deriving an iodine concentration in an artery feeding a volume of interest (VOI) in the multi-faceted CT data. The method further includes determining an effective atomic number of a spatial distribution in the VOL calculating a perfused blood volume of the VOI using the iodine concentration and the effective atomic number, and generating a report of the perfused blood volume of the VOI.

In an embodiment, a method (100) is described. The method comprises receiving (102) data corresponding to a plurality of radiographic imaging slices of a body. The method further comprises determining (104) a position of a needle inserted in the body. The determination is based on combining information from at least one of the radiographic imaging slices comprising an indication of a first portion of the needle outside the body and at least one other of the radiographic imaging slices comprising an indication of a second portion of the needle inside the body. A combined needle region is generated by merging data corresponding to a position of the first portion of the needle outside the body with data corresponding to a position of the second portion of the needle inside the body. The method further comprises generating (106) display data for providing a visual representation of the needle in an image of the body in combination with a visual representation of at least the first and second portions of the needle superimposed on the image. The image is in a plane that is digitally tilted with respect to a plane parallel to the plurality of radiographic imaging slices.

Imaging systems and methods for imaging assisted interventional procedure that receive images of a region of interest, that automatically detect in the images a contrast agent puff as it courses through the region of interest, and that generate a display including a video replay loop of contrast enhanced images based on the automatic detection of the contrast agent puff.

A processor superimposes and displays relevant information related to a medical image on the medical image so as to be switchable between display and hiding. The processor switches at least a part of the relevant information to be hidden in a case where another operation related to display or interpretation of the medical image is detected, the other operation being an operation other than a dedicated operation for switching between display and hiding of the relevant information while the relevant information is being displayed.

A system for constructing fluoroscopic-based three-dimensional volumetric data of a target area within a patient from two-dimensional fluoroscopic images including a structure of markers, a fluoroscopic imaging device configured to acquire a sequence of images of the target area and of the structure of markers, and a computing device. The computing device is configured to estimate a pose of the fluoroscopic imaging device for at least a plurality of images of the sequence of images based on detection of a possible and most probable projection of the structure of markers as a whole on each image of the plurality of images. The computing device is further configured to construct fluoroscopic-based three-dimensional volumetric data of the target area based on the estimated poses of the fluoroscopic imaging device.

A medical information processing system in an embodiment includes processing circuitry. The processing circuitry acquires an ultrasound image including an observation target and having additional information, positional information indicating a position of an ultrasound probe in a subject at time of collection of the ultrasound image, and a reference image obtained by taking an image of a region including the observation target at a time point other than the time of collection. The processing circuitry generates, based on the positional information, correspondence information in which the ultrasound image and the reference image are associated with each other. The processing circuitry causes an output unit to output the generated correspondence information.