Abstract: A system for forming an ad-hoc network among devices includes a wireless device that utilizes one or more connection protocols; a protocol bridging mechanism operating on one or more communication layers selected from the group of: an application layer, a transport layer, a data link layer, a physical layer and a network layer, wherein the one or more connection protocols connects to other wireless devices through the protocol bridging mechanism; and a controller stored within the wireless device. The system further includes a memory including program instructions executable by the controller that cause the controller to connect to the first nearby wireless device through the first communication protocol; connect to the second nearby wireless device through the second communication protocol; and transmit data between the first nearby wireless device and the second nearby wireless device through the protocol bridging mechanism.

Abstract: A system for forming an ad-hoc network among devices includes a wireless device that utilizes one or more connection protocols; a protocol bridging mechanism operating on one or more communication layers selected from the group of: an application layer, a transport layer, a data link layer, a physical layer and a network layer, wherein the one or more connection protocols connects to other wireless devices through the protocol bridging mechanism; and a controller stored within the wireless device. The system further includes a memory including program instructions executable by the controller that cause the controller to connect to the first nearby wireless device through the first communication protocol; connect to the second nearby wireless device through the second communication protocol; and transmit data between the first nearby wireless device and the second nearby wireless device through the protocol bridging mechanism.

Abstract: Example apparatus and methods provide improved quantitative T2 mapping for magnetic resonance imaging (MRI). Conventional T2 (spin-spin) mapping in MRI may employ a spin echo with multiple echoes (SEMC) approach like the Carr-Purcell-Meiboom-Gill (CPMG) spin echo sequence. These conventional approaches may be negatively impacted by a slice profile effect that incorrectly and undesirably lowers the signal of a first echo and by a stimulated echo effect that incorrectly and undesirably raises the signal for even echoes. Example apparatus mitigate these issues by using a T2 preparation phase that uses three dimensional (3D) non-slice selective block RF pulses followed by a multi-echo data acquisition that uses an in-out k-space trajectory. The multi-echo acquisition may employ k-space segmentation to acquire one line of partition encodings per T2 preparation phase.

Abstract: A system acquires MR image data of a portion of patient anatomy associated with spin lattice relaxation time in a rotating frame using an RF (Radio Frequency) signal generator and a magnetic field gradient generator. The RF (Radio Frequency) signal generator generates RF excitation pulses in anatomy and enables subsequent acquisition of associated RF echo data. The magnetic field gradient generator generates anatomical volume select magnetic field gradients for phase encoding and readout RF data acquisition in a three dimensional (3D) anatomical volume. The RF signal generator and the gradient generator use in order, a saturation pulse, a T1 spin lattice relaxation rotating frame preparation pulse sequence and a spoiler gradient, in acquiring image data of the 3D volume showing luminance contrast associated with T1 spin lattice relaxation in a rotating frame.

Abstract: Example apparatus and methods provide improved quantitative T2 mapping for magnetic resonance imaging (MRI). Conventional T2 (spin-spin) mapping in MRI may employ a spin echo with multiple echoes (SEMC) approach like the Carr-Purcell-Meiboom-Gill (CPMG) spin echo sequence. These conventional approaches may be negatively impacted by a slice profile effect that incorrectly and undesirably lowers the signal of a first echo and by a stimulated echo effect that incorrectly and undesirably raises the signal for even echoes. Example apparatus mitigate these issues by using a T2 preparation phase that uses three dimensional (3D) non-slice selective block RF pulses followed by a multi-echo data acquisition that uses an in-out k-space trajectory. The multi-echo acquisition may employ k-space segmentation to acquire one line of partition encodings per T2 preparation phase.

Abstract: A system assesses quality of an image of human anatomical components in the presence of a metallic object. The system comprises an image processor for selecting an imaging protocol to use in imaging a test unit in response to data indicating a metal type employed in the test unit. The test unit includes, at least one object of the metal type used for a medical implant, an object comprising water and an object representing human fat. The water object and fat object are less than 3 centimeters, for example, distant from the metal object.

Abstract: In a magnetic resonance method and apparatus, the magnetic resonance apparatus is operated according to a SEMAC (Slice Encoding for Metal Artifact Correction) sequence, and, before executing the SEMAC sequence, a scout sequence is implemented, which is a SEMAC sequence but without phase encoding in the direction perpendicular to the slice selection direction. The number of SEMAC coding steps can then be determined before executing the SEMAC sequence, so that an unnecessarily high number of SEMAC coding steps is avoided.

Abstract: A method provides motion corrected MR image data in an MR imaging system. The method employs an imaging method for acquiring k-space data of a k-space data array during an imaging scan and the k-space data represents image data of a patient anatomical region. The method acquires k-space data associated with a central region of the k-space data array and subsequently acquires k-space data external to the central region of the k-space data array. The method acquires a motion signal indicating respiratory motion at least during the acquisition of the k-space data external to the central region and compares the motion signal with a predetermined threshold. The method identifies acquired k-space data corresponding to acquisition periods when the motion signal exceeds the threshold and excludes use of the identified acquired k-space data in image reconstruction using the remaining acquired k-space data.

Abstract: Apparatus, methods, and other embodiments associated with self-justification fitting for magnetic resonance imaging (MRI) relaxation parameter quantification are described. One example nuclear magnetic resonance (NMR) apparatus includes a self-justification fitting logic configured to selectively include and exclude data points from a set of data points associated with NMR signals based, at least in part, on their impact on a fit attribute (e.g., standard deviation). In one embodiment, the self-justification is configured to select a subset of data points from the set of data points as a function of values for a fit attribute computed from fitting at least two different subsets of data points from the set of data points to a known NMR signal evolution.

Abstract: A system acquires MR image data of a portion of patient anatomy associated with spin lattice relaxation time in a rotating frame using an RF (Radio Frequency) signal generator and a magnetic field gradient generator. The RF (Radio Frequency) signal generator generates RF excitation pulses in anatomy and enables subsequent acquisition of associated RF echo data. The magnetic field gradient generator generates anatomical volume select magnetic field gradients for phase encoding and readout RF data acquisition in a three dimensional (3D) anatomical volume. The RF signal generator and the gradient generator use in order, a saturation pulse, a T1 spin lattice relaxation rotating frame preparation pulse sequence and a spoiler gradient, in acquiring image data of the 3D volume showing luminance contrast associated with T1 spin lattice relaxation in a rotating frame.

Abstract: A system assesses quality of an image of human anatomical components in the presence of a metallic object. The system comprises an image processor for selecting an imaging protocol to use in imaging a test unit in response to data indicating a metal type employed in the test unit. The test unit includes, at least one object of the metal type used for a medical implant, an object comprising water and an object representing human fat. The water object and fat object are less than 3 centimeters, for example, distant from the metal object.

Abstract: A method provides motion corrected MR image data in an MR imaging system. The method employs an imaging method for acquiring k-space data of a k-space data array during an imaging scan and the k-space data represents image data of a patient anatomical region. The method acquires k-space data associated with a central region of the k-space data array and subsequently acquires k-space data external to the central region of the k-space data array. The method acquires a motion signal indicating respiratory motion at least during the acquisition of the k-space data external to the central region and compares the motion signal with a predetermined threshold. The method identifies acquired k-space data corresponding to acquisition periods when the motion signal exceeds the threshold and excludes use of the identified acquired k-space data in image reconstruction using the remaining acquired k-space data.

Abstract: Apparatus, methods, and other embodiments associated with self-justification fitting for magnetic resonance imaging (MRI) relaxation parameter quantification are described. One example nuclear magnetic resonance (NMR) apparatus includes a self-justification fitting logic configured to selectively include and exclude data points from a set of data points associated with NMR signals based, at least in part, on their impact on a fit attribute (e.g., standard deviation). In one embodiment, the self-justification is configured to select a subset of data points from the set of data points as a function of values for a fit attribute computed from fitting at least two different subsets of data points from the set of data points to a known NMR signal evolution.

Abstract: An apparatus and method for obtaining diffusion weighted magnetic resonance images (DW-MRI) is described. The properties of the diffusion tensor in tissue are measured by applying a diffusion weighting gradient oriented along a plurality of measurement axes. The value of the magnetic field is increased by using as many of the magnetic gradient coils as are effective in contributing the gradient field strength along the axis being. In regions where the magnetic field gradient is increased, the echo time (TE) may be decreased, increasing the signal-to-noise ratio of the measurements. Alternatively, the number of measurements than are averaged to achieve a particular image quality may be decreased, reducing the patient exposure time.

Abstract: An apparatus and method for obtaining diffusion weighted magnetic resonance images (DW-MRI) is described. The properties of the diffusion tensor in tissue are measured by applying a diffusion weighting gradient oriented along a plurality of measurement axes. The value of the magnetic field is increased by using as many of the magnetic gradient coils as are effective in contributing the gradient field strength along the axis being. In regions where the magnetic field gradient is increased, the echo time (TE) may be decreased, increasing the signal-to-noise ratio of the measurements. Alternatively, the number of measurements than are averaged to achieve a particular image quality may be decreased, reducing the patient exposure time.

Abstract: A filtering method and apparatus for selectively filtering a gray scale angiographic image volume (54) that images vascular structures and that also contains extraneous non-vascular contrast is disclosed. A minimum vessel width parameter Wmin (70) is selected. A maximum vessel width parameter Wmax (132) is selected. A range of widths (66) are selected such that each vessel width parameter Wi (194) lies between Wmin (70) and Wmax (132) inclusive. For each Wi (194), an image Ii(x,y,z) (198) is generated that selectively retains imaged vascular structures of diameter Wi (194). The images Ii(x,y,z) (198) are combined to form a filtered image IF(x,y,z) (64) that selectively images the vascular structures.

Abstract: To produce a black body angiographic image representation of a subject (42), an imaging scanner (10) acquires imaging data that includes black blood vascular contrast. A reconstruction processor (38) reconstructs a gray scale image representation (100) from the imaging data. A post-acquisition processor (46) transforms (130) the image representation (100) into a pre-processed image representation (132). The processor (46) assigns (134) each image element into one of a plurality of classes including a black class corresponding to imaged vascular structures, bone, and air, and a gray class corresponding to other non-vascular tissues. The processor (46) averages (320) intensities of the image elements of the gray class to obtain a mean gray intensity value (322), and replaces (328) the values of image elements comprising non-vascular structures of the black class with the mean gray intensity value.

Abstract: A magnetic resonance imaging method and apparatus includes a navigator region defined within the subject by selective excitation. Blood flow is measured within the selected region using the principles of phase contrast MR angiography. A cardiac cycle plot is constructed from Fourier transformed data that represents measured velocity of blood flow through the navigator region as a function of time. On the basis of the cardiac cycle plot and the navigator measurements, data acquisition is synchronized or gated to portions of the cardiac cycle.

Abstract: A magnetic resonance angiographic method includes acquiring (70) high resolution volume image data comprising data (74) corresponding to a plurality of high resolution image slices, and acquiring (72) data corresponding to at least one vessel identification image slice (76), said acquired data having selectively enhanced contrast for one of arteries and veins. A high resolution volume image representation (80) is reconstructed from the acquired high resolution volume image data (74). At least one vessel identification slice image representation (82) is reconstructed from the acquired data corresponding to at least one vessel identification image slice (76). At least one of an artery starting point (86) and a vein starting point (88) is identified based on the vessel identification slice image representation (82).

Abstract: A two-dimensional slice formed of pixels (376) is extracted from the angiographic image (76) after enhancing the vessel edges by second order spatial differentiation (78). Imaged vascular structures in the slice are located (388) and flood-filled (384). The edges of the filled regions are iteratively eroded to identify vessel centers (402). The extracting, locating, flood-filling, and eroding is repeated (408) for a plurality of slices to generate a plurality of vessel centers (84) that are representative of the vascular system. A vessel center (88) is selected, and a corresponding vessel direction (92) and orthogonal plane (94) are found. The vessel boundaries (710) in the orthogonal plane (94) are identified by iteratively propagating (704) a closed geometric contour arranged about the vessel center (88). The selecting, finding, and estimating are repeated for the plurality of vessel centers (84). The estimated vessel boundaries (710) are interpolated (770) to form a vascular tree (780).