Abstract: A method of deriving blood flow parameters from a moving three-dimensional (3D) model of a blood vessel includes determining a reference vascular cross-sectional plane through a location of a lumen in a moving 3D model of the blood vessel at one time within the model, determining a plurality of target vascular cross-sectional planes at multiple times via temporal tracking of the reference plane based on a displacement field, determining a plurality of contours based on an intersection of the target vascular cross-sectional planes with the moving 3D vessel model at multiple times within the model, and determining a blood flow parameter of the vessel from intersections of each contour of a given one of the times with a phase contrast magnetic resonance (PC-MRI) image of the blood vessel from the corresponding time.

Abstract: A reconstructed image is rendered from a set of MRI data by first estimating an image with an area which does not contain artifacts or has an artifact with a relative small magnitude. Corresponding data elements in the estimated image and a trial image are processed, for instance by multiplication, to generate an intermediate data set. The intermediate data set is transformed and minimized iteratively to generate a reconstructed image that is free or substantially free of artifacts. In one embodiment a Karhunen-Loeve Transform (KLT) is used. A sparsifying transformation may be applied to generate the reconstructed image. The sparsifying transformation may be also not be applied.

Abstract: In MR imaging of a predetermined volume segment of a living examination subject, the examination subject is stimulated with a defined stimulation pattern, MR data of the predetermined volume segment, are acquired, and MR images based on the MR data are generated that depend on the stimulation pattern. The predetermined volume segment is an internal organ or muscle tissue of the examination subject.

Abstract: A method and system for retrospective image combination for free-breathing magnetic resonance (MR) images is disclose. A free-breathing cardiac MR image acquisition including a plurality of frames is received. A key frame is selected of the plurality of frames. A deformation field for each frame to register each frame with the key frame. A weight is determined for each pixel in each frame based on the deformation field for each frame under a minimum total deformation constraint. A combination image is then generated as a weighted average of the frames using the weight determined for each pixel in each frame.

Abstract: In a control method and a control unit for context-specific determination of at least one DESIRED perspective upon rendering of medical image data at a monitor, a graphical symbol is generated at a user interface dynamically and depending on an image status in order to detect a perspective control signal, and is used to control the rendering.

Abstract: A method for gathering information relating to at least one object positioned on a patient positioning device of a medical imaging device is provided. The method includes the following steps: gathering by optical means of 3-D image data relating to the object positioned on the patient positioning device by means of a 3-D image data recording unit, transferring the gathered 3-D image data from the 3-D image data recording unit to an evaluating unit, determining information relating to the object positioned on the patient positioning device based on the 3-D image data by means of the evaluating unit, generating output information based on the determined information relating to the object positioned on the patient positioning device, and outputting the output information relating to the object positioned on the patient positioning device.

Abstract: A system supports medical imaging compliance with guideline and reimbursement requirements using at least one repository and a compliance processor. The at least one repository associates information including, specific reimbursement requirements of a patient insurance company with an imaging protocol compliant with predetermined guidelines for imaging a particular anatomical feature and with a specific type of imaging device and with multiple different steps of the imaging protocol. The compliance processor uses the information in, determining whether a particular imaging protocol for imaging a particular anatomical feature of a particular patient on a particular type of imaging device is compliant with the guidelines and the reimbursement requirements and identifying at least one of, (a) a missing step and (b) an incorrect step, in the particular imaging protocol.

Abstract: A method for symmetric and inverse-consistent registration of a pair of digital images includes calculating a first update of a forward transformation of a first digital image to a second digital image from a previous update of the forward transformation and a gradient of a cost function of the first and second digital images, calculating a first update of a backward transformation of the second digital image to the first digital image from an inverse of the first update of the forward transformation, calculating a second update of the backward transformation from first update of the backward transformation and the gradient of a cost function of the second and first digital images, and calculating a second update of the forward transformation from an inverse of the second update of the backward transformation.

Abstract: A system receives cardiac cine MR images consists of multiple slices of the heart over time. A series of short axis images slices are received. Long axis images are also received by the system, wherein a base plane defined by landmark points is detected. An intersection of the base plane with a contour of a heart chamber is determined for a plurality of slices in the short axis image. A volume for each of the contour slices covering the heart chamber, including for contours that are limited by base plane intersections, is evaluated. All slice volumes are summed to determine a total volume of the chamber. In one embodiment the chamber is a left ventricle and the landmark is a mitral valve. An ejection factor is determined.

Abstract: A method and system for segmenting multiple organs in medical image data is disclosed. A plurality of landmarks of a plurality of organs are detected in a medical image using an integrated local and global context detector. A global posterior integrates evidence of a plurality of image patches to generate location predictions for the landmarks. For each landmark, a trained discriminative classifier for that landmark evaluates the location predictions for that landmark based on local context. A segmentation of each of the plurality of organs is then generated based on the detected landmarks.

Abstract: A system dynamically improves quality of medical images using at least one processing device including an image analyzer, a correction processor and a message generator. The image analyzer automatically parses and analyzes data representing an image of a particular anatomical feature of a patient acquired by a medical image acquisition device to identify defects in the image by examining the data representing the image for predetermined patterns associated with image defects. The correction processor uses a predetermined information map associating image defects with corresponding corrective image acquisition parameters to determine corrected image acquisition parameters for use in re-acquiring an image using the image acquisition device in response to an identified defect. The message generator generates a message for presentation to a user indicating an identified defect and suggesting use of the corrected image acquisition parameters for re-acquiring an image.

Abstract: A method for cardiac segmentation in magnetic resonance (MR) cine data, includes providing a time series of 3D cardiac MR images acquired at a plurality of phases over at least one cardiac cycle, in which each 3D image includes a plurality of 2D slices, and a heart and blood pool has been detected in each image. Gray scales of each image are analyzed to compute histograms of the blood pool and myocardium. Non-rigid registration deformation fields are calculated to register a selected image slice with corresponding slices in each phase. Endocardium and epicardium gradients are calculated for one phase of the selected image slice. Contours for the endocardium and epicardium are computed from the gradients in the one phase, and the endocardium and epicardium contours are recovered in all phases of the selected image slice. The recovered endocardium and epicardium contours segment the heart in the selected image slice.

Abstract: A reconstructed image is rendered of a patient by a processor from a set of undersampled MRI data by first subtracting two repetitions of the acquired data in k-space to create a third dataset. The processor reconstructs the image by minimizing an objective function under a constraint related to the third dataset, wherein the objective function includes applying a Karhunen-Loeve Transform (KLT) to a temporal dimension of data. The objective function under the constraint is expressed as arg minf{??(f)?1 subject to ?Af?y?2??}. The reconstructed image is an angiogram which may be a 4D angiogram. The angiogram is used to diagnose a vascular disease.

Abstract: A method for automatic femur segmentation and condyle line detection. The method includes: scanning a knee of a patient with medical imaging equipment to obtain 3D imaging data with such equipment; processing the obtained 3D imaging data in a digital processor to determine two lines tangent to the bottom of the knee condyles in an axial and a coronal plane; and automatically scanning the patient in the defined plane. The processing includes: determining an approximate location of the knee; using the determined the location to define a volume of interest; segmenting the femur in the defined volume of interest; and determining a bottom point on the femur portion on a right side and a left side of the segmented femur in an axial and a coronal slice to determine the two lines.

Abstract: A method for automatically determining a field of view for performing a subsequent medical imaging study includes acquiring one or more preliminary images. A body mask is generated by thresholding the preliminary images and identifying a largest connected component. A boundary mask is obtained from the boundary of the generated body mask. A rectangular bounding box is fit to the obtained boundary mask. The rectangular bounding box is used as a field of view for performing a subsequent medical imaging study.

Abstract: Disclosed is a method for determining and displaying at least one piece of information on a target volume, especially in a human body, the information being obtained from an image record. At least one embodiment of the method includes: a first and at least one second image record of a target zone encompassing the target volume are recorded, the first image record having a higher contrast regarding the boundaries of the target volume, and the first and the second image record being registered together; the target volume is segmented in the first image record; target volume image data.

Abstract: Magnetic resonance reconstruction includes motion compensation. Inverse-consistent non-rigid registration is used to determine motion between shots. The motion is incorporated into reconstruction. The incorporation compensates for the motion resulting from the period over which the MR data is acquired.

Abstract: A method for performing motion compensation in a series of magnetic resonance (MR) images includes acquiring a set of MR image frames spanning different points along an MR recovery curve. A motion-free synthetic image is generated for each of the acquired MR image frames using prior knowledge pertaining to an MR recovery curve. Each of the acquired MR images is registered to its corresponding generated synthetic images. Motion within each of the acquired MR image is corrected based on its corresponding generated synthetic image that has been registered thereto.

Abstract: A method including receiving an image sequence, wherein the image sequence includes a plurality of two-dimensional (2D) image frames of an organ arranged in a time sequence; constructing a three-dimensional (3D) volume by stacking a plurality of the 2D image frames in time order; detecting a best bounding box for a target of interest in the 3D volume, wherein the best bounding box is specified by a plurality of parameters including spatial and temporal information contained in the 3D volume; and determining the target of interest from the best bounding box.

Abstract: A method for generating a positron emission tomography (PET) attenuation correction map from magnetic resonance (MR) images includes segmenting a 3-dimensional (3D) magnetic resonance (MR) whole-body image of a patient into low-signal regions, fat regions, and soft tissue regions; classifying the low-signal regions as either lungs, bones, or air by identifying lungs, identifying an abdominal station, and identifying a lower body station; and generating an attenuation map from the segmentation result by replacing the segmentation labels with corresponding representative attenuation coefficients.