Abstract: A magnetic resonance imaging (MRI) system includes an internet protocol (IP) communication system for communicating IP-based communication data, an audio/video output, and an audio/video source. The MRI system also includes an audio/video/IP gateway device with multiple non-IP interfaces operable to receive and output audio/video data. The non-IP interfaces use non-IP protocols, while an IP interface connected to the communication system uses a predefined audio/video IP protocol. A controller is operable to convert received audio/video data between the non-IP and IP protocols, output converted audio/video data via the IP interface in IP protocol, and output converted audio/video data via the non-IP interfaces using the corresponding non-IP protocol.

Abstract: Techniques are described for providing image-based operational decision support. The technique includes providing initial imaging data from a preceding examination of a patient, determining clinical findings by automated processing of the initial imaging data, generating decision data at least comprising a decision whether a further recording of a number of images is necessary, and generating a suggested set of imaging parameter values for recording this number of images. The decision data may be based on the determined clinical findings, and the technique may further include outputting the suggested set of imaging parameter values for recording a number of images of the patient. Also described are a related clinical decision system, a decision module, and a related medical imaging system.

Abstract: A system for standardized MRI examinations with patient-centric scan workflow adaptations including: a protocol management system for setup and/or to maintain scan programs and/or scan protocols centrally; a scan queue designed to provide a representation of past and planned scan workflow steps; and a scan workflow guidance system which is configured to use a preconfigured scan protocol and/or scan program by patient specific adaptions.

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.

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 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 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 clinical parameter derivation and adaptive flow acquisition within a sequence of magnetic resonance images includes commencing an acquisition of a sequence of images. One or more landmarks are automatically detected from within one or more images of the sequence of images. The detected one or more landmarks are propagated across subsequent images of the sequence of images. A plane is fitted to the propagation of landmarks. The positions of landmarks or alternatively the position of the fitted plane within the sequence of images is used for derivation of clinical parameters such as tissue velocities and/or performing adaptive flow acquisitions to measure blood flow properties.

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 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: 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 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 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: 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.