Abstract: Ultrasound data is simulated using magnetic resonance (MR) elastography. MR elastography provides tissue characteristic information, such as elastic modulus, velocity, or stiffness. This tissue characteristic information indicates a density or viscosity of the tissue, allowing simulation of ultrasound data with MR acquired data. The same MR imaging system may be used to acquire the MR elastography and pre-operative anatomy information. The actual ultrasound information may be registered with simulated ultrasound information for registration of the actual ultrasound information with the MR anatomy information.

Abstract: A method (200, 300) and system (100) for performing real-time, dynamic overlays on fluoroscopic images to aid in navigation and localization during medical procedures.

Abstract: A method and system for visualizing the spine in 3D medical images is disclosed. A spinal cord centerline is automatically determined in a 3D medical image volume, such as a CT volume. A reformatted image volume is then generated based on the spinal cord centerline. The reformatted image volume can be a straightened spine volume or a Multi-planar Reconstruction (MPR) based volume that follows the natural curve of the spine. The reconstructed volume can be displayed as 2D slices or 3D volume renderings.

Abstract: A method for grouping airway and artery pairs, includes: computing a two-dimensional (2D) cross-section of an airway; identifying regions of high-intensity in the 2D cross-section; computing a first indicator for each of the high intensity regions, wherein the first indicator is an orientation measure of the high intensity region with respect to the airway; computing a second indicator for each of the high intensity regions, wherein the second indicator is a circularity measure of the high intensity region; computing a third indicator for each of the high intensity regions, wherein the third indicator is a proximity measure of the high intensity region with respect to the airway; summing the first through third indicators for each of the high intensity regions to obtain a score for each of the high intensity regions; and determining which of the high intensity regions is an artery corresponding to the airway based on its score.

Abstract: A method for the detection of a balloon catheter within a fluoroscopic image, including: removing noise from a fluoroscopic image; detecting edges of a balloon catheter in the fluoroscopic image, wherein the detected edges include subsets of connected edges; extracting an edge subset from the subsets of connected edges; fitting a model to the extracted edge subset; removing outliers of the extracted edge subset based on the fitting of the model; adding the extracted edge subset without the outlier to a data set; repeating the extracting, fitting, removing and adding steps for the remainder of the subsets of connected edges; and fitting the model to the data set, wherein the data set is indicative of the balloon catheter.

Abstract: A method for segmenting image data within a data processing system includes acquiring an image. One or more seed points are established within the image. An advection vector field is computed based on image influences and user input. A dye concentration is determined at each of a plurality of portions of the image that results from a diffusion of dye within the computed advection field. The image is segmented into one or more regions based on the determined dye concentration for the corresponding dye.

Abstract: A method (100) that registers a 3D heart volume (112, 114) obtained from either a pre-operative MR image or CT image (102) to an intra-operative fluoroscopic image using a mesh of the heart structure (106) as the basis for the registration.

Abstract: A method including receiving a first two-dimensional (2D) image; and applying a filter to the 2D image to produce a filtered image that identifies a circular object of interest, wherein the filter is based on the integral sum of the function S, where the filter output at point x is M ? ( x ) = ? ? y ? V ? ? S ? ( m , ? , r , y ) ? ? ? ? y which is obtained from the 2D image, the function S is represented by S(m,?,r,y)=S1(m)S2(?,r), where m is a magnitude of a gradient at location y, r is a radial distance from y to x, and ? is an angle between the gradient at location y and the radial distance from y to x, S 1 ? ( m ) = ( tan - 1 ? ( m - C 1 ) + ? 2 ) ? , ? s 2 ? ( ? , r ) = 1 ? ? 2 ? ? ? ? ? - ( r × sin ? ? ? ) 2 2 ? ? ? 2 × ? - r × sin ? ( 90 - ? ) C 2 - r × sin ? ( 90 - ? ) ? 1 ? ? 2 ? ? ? ? ? - x 2 2 ? ? ? 2 ? ? ? x , C1 depends

Abstract: A method for diagnosing pulmonary hypertension from phase-contrast magnetic resonance (MR) images includes providing a time series of one or more magnetic resonance (MR) flow images of a patient's mediastinum during one or more cardiac cycles, segmenting the pulmonary artery within each image of the times series of images, identifying the anterior wall and pulmonary valve within the segmented pulmonary artery, analyzing blood flow during a diastolic phase of the one or more cardiac cycles to determine a relative duration of blood flow, tstreamlines, during the diastolic phase, analyzing blood flow during a latter portion of a systolic phase and a subsequent diastolic phase of the one or more cardiac cycles to detect the presence and duration tvortex of a vortex, and diagnosing the presence of pulmonary hypertension from tstreamlines and tvortex.

Abstract: A method including displaying a three-dimensional (3D) image of a lung, receiving a selection of an airway of the lung and displaying a two-dimensional (2D) cross-section image of the airway perpendicular to the airway's long axis, wherein the display of the 2D cross-section image occurs almost immediately after the selection of the airway is received.

Abstract: A method for visualizing airways in chest images, includes: computing a distance map of a segmented bronchial tree; extracting data from the segmented bronchial tree using the distance map; and visualizing a three-dimensional (3D) image of the segmented bronchial tree color-coded according to the extracted data.

Abstract: A system and method for detecting an area of interest such as a pulmonary embolism in a structure of interest such as a vessel tree or airway tree are provided. The method comprises: segmenting image data of the structure of interest; and rendering two-dimensional images based on a function of the image data and the segmented image data within slabs defined by the segmented image data.

Abstract: A method for directed machine learning includes receiving features including intensity data and location data of an image, condensing the intensity data and the location data into a feature vector, processing the feature vector by a plurality of classifiers, each classifier trained for a respective trained class among a plurality of classes, outputting, from each classifier, a probability of the feature vector belong to the respective trained class, and assigning the feature vector a label according to the probabilities of the classifiers, wherein the assignment produces a segmentation of the image.

Abstract: A dynamic method (100) to better depict context among the different views of an imaging visualization application used by a medical workstation.

Abstract: A method (100) that evaluates the contours of patient airways and visualizes anatomical changes to the airways.

Abstract: An MRI method (10) to map the temperature of a bodily tissue using measurements of the tissue density.

Abstract: A branch extension method and system for segmenting airways in 3D image data is disclosed. An initial airway segmentation is obtained from the 3D image data. Terminal branches of segmented airways of the initial airway segmentation are identified. The segmentation of the terminal branches is then extended. The segmentation of the terminal branches can be extended using various segmentation techniques. This method can use complex segmentation techniques to extend the terminal branches without having a large impact to the overall speed of the segmentation.

Abstract: A method for determining a size of an airway lumen and a thickness of an airway wall includes: computing a centerline of an airway; computing a three-dimensional (3D) gradient of a volume of the airway within a first threshold; positioning a tube along the centerline; iteratively expanding the tube by increasing its radius until the radius of the tube reaches the first threshold; determining inner and outer radii of the tube by checking the 3D gradient computed along an x-axis and a y-axis of the tube at a boundary of the tube at each iteration; and fitting the tube to the airway by using the determined inner and outer radii, wherein the inner radius of the fit tube is half a diameter of the airway lumen and the outer radius of the fit tube minus the inner radius of the fit tube is a thickness of the airway wall.

Abstract: Disclosed is an algorithm for applying a morphological operation to an image. In one embodiment, the morphological operation is iteratively applied to a focal pixel of the image and to another pixel of the image. The other pixel is located at an offset with respect to the focal pixel. The offset is based on an operation count. In another embodiment, the algorithm includes performing a morphological operation on an image using a convex structuring element. A work structuring element having dimensions corresponding to the outer-most dimensions of the convex structuring element is iteratively applied to the image. The dimensions of the work structuring element are then adjusted to correspond to the remaining outer dimensions of the convex structuring element not yet covered by the previous work structuring element. The applying and adjusting steps are repeated until a predetermined number of morphological operations have been performed.

Abstract: A method for detecting and localizing mucus plugs in digitized lung images, includes providing a digitized lung image volume comprising a plurality of intensities corresponding to a 3-dimensional grid of points, extracting a bronchial tree from said lung image, said bronchial tree comprising a plurality of branching airways terminating at terminal points, providing a model of a 2-dimensional cross section of an airway, selecting an extended point beyond a terminal point of an airway branch in a direction of said airway branch, obtaining a 2-dimensional cross section I of size m×n points from said lung image about said selected point, processing said 2D cross section I by calculating a local neighborhood function for each point in the cross section and forming a union of all local neighborhood functions, and calculating a correlation between processed 2D cross section and said airway model, wherein said correlation is indicative of the presence of a mucus plug within said airway.