Abstract: A boundary in a medical image is segmented. To increase reproducibility, a multi-level segmentation approach is used. A boundary is detected based on a seed point. The boundary is used to construct a banded graph. Local segmentation is performed using the banded graph. Based on the local segmentation, a new seed point is found. The local segmentation identifies a consistent location for the seed point. The boundary detection is performed again using the new seed point.

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 propagation of myocardial infarction from delayed enhanced magnetic resonance imaging (DE-MRI) to cine MRI is disclosed. A reference frame is selected in a cine MRI sequence. Deformation fields are calculated within the cine MRI sequence to register the frames of the cine MRI sequence to the reference frame. A DE-MRI image having an infarction region is registered to the reference frame of the cine MRI sequence. The DE-MRI image may be registered to the infarction region using a hybrid registration algorithm that unifies both intensity and feature points into a single cost function. Infarction information in the DE-MRI image is then propagated cardiac phases of the frames in the cine MRI sequence based on the registration of the DE-MRI image to the reference frame and the plurality of deformation fields calculated within the cine MRI sequence.

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: 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 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: An exemplary embodiment of the present invention includes a method of detecting a left ventricle blood pool. The method includes: localizing a region of interest (ROI) in a three-dimensional temporal (3D+T) image based on motion information of each slice of the 3D image over time, thresholding the ROI to determine pixels of the ROI that correspond to blood, extracting connected components from the determined pixels, clustering the extracted connected components into groups based on criteria that are indicative of a blood pool of a left ventricle, and selecting one of the groups as the left ventricle blood pool.

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 boundary in a medical image is segmented. To increase reproducibility, a multi-level segmentation approach is used. A boundary is detected based on a seed point. The boundary is used to construct a banded graph. Local segmentation is performed using the banded graph. Based on the local segmentation, a new seed point is found. The local segmentation identifies a consistent location for the seed point. The boundary detection is performed again using the new seed point.

Abstract: The aorta and left atrium are localized from magnetic resonance data. The locations of the aorta and left atrium are detected jointly. The aorta and the left atrium are, at least in part, treated as one object. The detection may be from data representing a two-dimensional region. The two-dimensional region may be determined by first detecting the left ventricle from data representing a volume.

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: 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 automatically localizing left ventricle in medical image data includes acquiring a sequence of three-dimensional medical images spanning a cardiac cycle. Each of the images includes a plurality of two-dimensional image slices, one of which is defined as a template slice. The template slice of each medical image of the sequence is automatically cropped to include the heart and a margin around the heart based on temporal variations between pixels of the template slice throughout the sequence of medical images. The template slice of each medical image of the sequence is automatically contoured to determine the endo-cardial and epi-cardial boundaries for at least the end-diastolic and end-systolic phases. Localization information is generated for the left ventricle based on the determined endo-cardial and epi-cardial boundaries for at least the end-diastolic and end-systolic phases.

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: A method and system for propagation of myocardial infarction from delayed enhanced magnetic resonance imaging (DE-MRI) to cine MRI is disclosed. A reference frame is selected in a cine MRI sequence. Deformation fields are calculated within the cine MRI sequence to register the frames of the cine MRI sequence to the reference frame. A DE-MRI image having an infarction region is registered to the reference frame of the cine MRI sequence. The DE-MRI image may be registered to the infarction region using a hybrid registration algorithm that unifies both intensity and feature points into a single cost function. Infarction information in the DE-MRI image is then propagated cardiac phases of the frames in the cine MRI sequence based on the registration of the DE-MRI image to the reference frame and the plurality of deformation fields calculated within the cine MRI sequence.

Abstract: A method and system for automated view planning for cardiac magnetic resonance imaging (MRI) acquisition is disclosed. The method and system automatically generate a full scan prescription using a single 3D MRI volume. The left ventricle (LV) is segmented in the 3D MRI volume. Cardiac landmarks are detected in the automatically prescribed slices. A full scan prescription, including a short axis stack and 2-chamber, 3-chamber, and 4-chamber views, is automatically generated based on cardiac anchors provided by the segmented left ventricle and the detected cardiac landmarks in the 3D MRI volume.

Abstract: A method for identifying a region of interest within a time sequence of images includes acquiring a time sequence of images comprising a plurality of image frames. Image segmentation is performed to segment a region of interest (ROI) from within each of the plurality of image frames of the time sequence of images. Manual edits are received for the ROI within one or more of the plurality of image frames. The manual edits are propagated to other image frames of the plurality of images. An extent to which each of the manual edits are propagated to other image frames is dependent upon a transformation function or deformation field used to propagate the manual edits and a weighing factor that is influenced by a distance in time between the other image frames and the frames that have been manually edited.

Abstract: A method for correcting the background phase in magnetic resonance phase contrast flow images includes providing a time series of velocity encoded magnetic resonance images of a patient, where the time series of velocity encoded images comprises for each time point a phase contrast image where a pixel intensity is proportional to a flow velocity, measuring a change of intensity for each pixel over the time series of phase contrast images, identifying pixels with a low measure of temporal change as stationary pixels, and calculating a correction field for the stationary pixels, where the correction field represents a background phase to be subtracted from the phase contrast image.