A radiological imaging device configured to analyze a limb includes a first module that includes a source configured to emit radiation, a second module that includes a detector configured to receive radiation from the source that has passed through the limb, a control station connected to the first and second modules for controlling movement of the first and second modules and acquiring images from the second module, and a platform having an outer support surface to support the first and second modules. The control station includes a casing and a connecting member that is connected to the casing to attach the platform. The platform is suitable to rotate around an axis approximately parallel to the outer surface.

A patient-specific assessment of fracture probability for the femur proximal end is provided. 3D locations of the femur head center, a point on the femoral shaft center, and the femoral intercondylar notch are determined from a clinical image. A frontal plane, a perpendicular thereunto and a bone shaft axis are determined from the 3D locations. An FEA coordinate system is defined from the frontal plane, the perpendicular and the axis. Two FEA analyses are performed, one for neck fracture and one for pertrochanteric fracture, with the same displacement constraints and the same load magnitude but different load angles. The femur proximal end is divided into four anatomically-based regions. For each region and each load, maximum tensile and compressive principal strains are determined and, based on the body weight and the principal strains, a likelihood of fracture is obtained. The minimum of these 8 likelihoods gives the probability of fracture.

An image processing apparatus, an image display system, an image processing method, and a program by which it is possible to display an optimum three dimensional image when display is switched from a two dimensional tomographic image to a three dimensional image are provided. The processor (14) outputs a tomographic image display signal representing a two dimensional tomographic image included in a first tomographic image group based on first imaging data obtained by imaging a subject, extracts a second tomographic image group having a smaller interval between tomographic images than the first tomographic image group, on the basis of second imaging data acquired in imaging corresponding to the imaging for acquiring the first imaging data, if a display switching signal indicating switching from display of the two dimensional tomographic image to display of a three dimensional image is acquired, and outputs a three dimensional image display signal representing a three dimensional image generated on the basis of the extracted second tomographic image group.

A transformable imaging system configured to operate in at least two configurations. A first configuration may be open and a second configuration may be closed. The closed configuration may allow for imaging in along an arc greater than 180 degrees.

A computer-implemented method for automated classification of 3D image data of teeth includes a computer receiving one or more of 3D image data sets where a set defines an image volume of voxels representing 3D tooth structures within the image volume associated with a 3D coordinate system. The computer pre-processes each of the data sets and provides each of the pre-processed data sets to the input of a trained deep neural network. The neural network classifies each of the voxels within a 3D image data set on the basis of a plurality of candidate tooth labels of the dentition. Classifying a 3D image data set includes generating for at least part of the voxels of the data set a candidate tooth label activation value associated with a candidate tooth label defining the likelihood that the labelled data point represents a tooth type as indicated by the candidate tooth label.

A computing system (118) includes a computer readable storage medium (122) with computer executable instructions (124), including a biophysical simulator (126) and an electrocardiogram signal analyzer (128). The computing system further includes a processor (120) configured to execute the electrocardiogram signal analyzer determine myocardial infarction characteristics from an input electrocardiogram and to execute the biophysical simulator to simulate a fractional flow reserve or an instant wave-free ratio index from input cardiac image data and the determined myocardial infarction characteristics.

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.

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.

According to one embodiment, a medical image processing apparatus includes processing circuitry. The processing circuitry designates a region of interest in a first tomogram among multiple tomograms which are based on tomosynthesis imaging performed with a subject compressed in a first direction. The processing circuitry specifies a second tomogram corresponding to the region of interest from among multiple tomograms which are based on tomosynthesis imaging performed with the subject compressed in a second direction different from the first direction.

The invention provides, in some aspects, a system for implementing a rule derived basis to display image sets. In various embodiments of the invention, the selection of the images to be displayed, the layout of the images, as well as the rendering parameters and styles can be determined using a rule derived basis. In an embodiment of the present invention, the user is presented with images displayed based on their preferences without having to first manually adjust parameters.