Koninklijke Philips Corporation N.v.

Picker International, Inc.

Siemens Medical Solutions Usa, Inc.

Other

Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Case Western Reserve University

Philips Medical Systems (cleveland), Inc.

Kecheng Liu

Jasjit S Suri

Tiejun Zhao

Paul M Margosian

Mark A Griswold

Gordon D DeMeester

Dan Ma

Mark J Loncar

Dee H Wu

Yansun Xu

Jian Lin

Thorsten Feiweier

Michael Burl

Jukka Ilmari Tanttu

James A Halamek

Thomas S Cull

Jing An

Abraham Padua, Jr

Laura M Reden

Neil Palmer

YongMing Dai

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. While conventional systems mix T2 preparation and multi-echo acquisition, example apparatus and methods separate T2 preparation and multi-echo acquisition.

Magnetic resonance imaging (MRI) with artifact-free T2 mapping

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.

System for reducing artifacts in imaging in the presence of a spin-lock radio-frequency field

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.

Metallic object MR imaging quality control system

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.

Motion compensated MR imaging system

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.

Relaxometry quantification self-justification fitting

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.

Method and apparatus for diffusion tensor magnetic resonance imaging

A filtering method and apparatus for selectively filtering a gray scale angiographic image volume () that images vascular structures and that also contains extraneous non-vascular contrast is disclosed. A minimum vessel width parameter W() is selected. A maximum vessel width parameter W() is selected. A range of widths () are selected such that each vessel width parameter W() lies between W() and W() inclusive. For each W(), an image I(x,y,z) () is generated that selectively retains imaged vascular structures of diameter W(). The images I(x,y,z) () are combined to form a filtered image I(x,y,z) () that selectively images the vascular structures.

Method and apparatus for three-dimensional filtering of angiographic volume data

To produce a black body angiographic image representation of a subject (), an imaging scanner () acquires imaging data that includes black blood vascular contrast. A reconstruction processor () reconstructs a gray scale image representation () from the imaging data. A post-acquisition processor () transforms () the image representation () into a pre-processed image representation (). The processor () assigns () 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 () averages () intensities of the image elements of the gray class to obtain a mean gray intensity value (), and replaces () the values of image elements comprising non-vascular structures of the black class with the mean gray intensity value.

Black blood angiography method and apparatus

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.

Blood flow gated MRI

A magnetic resonance angiographic method includes acquiring () high resolution volume image data comprising data () corresponding to a plurality of high resolution image slices, and acquiring () data corresponding to at least one vessel identification image slice (), said acquired data having selectively enhanced contrast for one of arteries and veins. A high resolution volume image representation () is reconstructed from the acquired high resolution volume image data (). At least one vessel identification slice image representation () is reconstructed from the acquired data corresponding to at least one vessel identification image slice (). At least one of an artery starting point () and a vein starting point () is identified based on the vessel identification slice image representation (). Preferably, the method further includes defining () an initial surface that encloses the at least one starting point (), and iteratively growing () the initial surface () until the surface essentially coincides with the boundaries of the vascular system.

Automatic vessel indentification for angiographic screening

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

Angiography method and apparatus

An imaging system and method enables 3-D direct segmentation from a series of spatially offset 2-D image slices in a volume scan. The algorithm first smoothes and preserves the interface edges of the image volume using Bottom-Hat gray scale morphological transform followed by 3-D segmentation using fast 3-D level sets by preserving topology constraints, for example, cortical thickness in a brain volume. The method inputs opposite polarity spheres (contracting and expanding spheres) which morph into shapes within the volume using a surface propagation technique. The speed of propagation is controlled by the likelihood statistical component derived under constraints. During the propagation polygonalization extracts the zero-level surface set. The field distribution is computed using the improved shortest distance method or polyline distance method. The morphing algorithm then morphs the input concentric spheres into interface surfaces such as WM-GM and GM-CSF with cortical constraint. The system is optimized by computing the 3-D field in the narrow band on the morphing spheres.

Image segmentation of embedded shapes using constrained morphing

A method of a conducting a magnetic resonance imaging experiment with an interleaved phase encoding acquisition includes setting an interleave factor which is an imaging parameter that represents the number of interleaves in the interleaved phase encoding acquisition, and determining an artifact suppression factor. The artifact suppression factor is an imaging parameter that represents an amount of SBA suppression achieved in the imaging experiment being conducted. The method further includes determining if the artifact suppression factor falls within a range. When the artifact suppression factor falls outside the range, notification is provided, and when the artifact suppression factor falls inside the range, a sequence of progression is determined for an excitation slab employed in the imaging experiment.

Interleaved phase encoding acquisition for MRI with controllable artifact suppression and flexible imaging parameter selection

To image flowing materials, magnetic resonance preconditioning pulses are applied in an upstream region ( ). For scanning a subject, an RF pulse calibration sequence is performed by generating a corresponding magnetic resonance data line ( ) in each of a plurality of slices ( ) along a vessel. A processor ( ) determines a signal intensity for each slice ( ), fits the intensities for the family of slices to a curve ( ), and adjusts an RF pulse profile with spatial position in accordance with the curve which is dynamically dependent on the scanned subject. In a subsequent imaging sequence with the adjusted tip angles, data lines from each of the slices are received ( ) and reconstructed ( ) into an image representation stored in the memory ( ).

Flow adaptive guided determination of imaging parameters for 3D magnetic resonance angiography

A region of interest of a subject is disposed in an imaging region ( ) of a magnetic resonance imaging apparatus. A contrast material ( ) is injected into the subject. An operator initiates a series of fast scan imaging sequences to track the position for entry of the contrast material, into the region of interest. A trajectory through a k-space is selected for the fast scan imaging sequences that both generates data lines for the fast scan images and oversamples a common data point ( ). A peak intensity of the oversampled common point ( ) indicates that the bolus of contrast agent ( ) has arrived. A sequence controller ( ) initiates a diagnostic imaging sequence ( ). The operator views the fast scan image and has the option to abort the diagnostic sequence ( ) if the fast scan image does not verify that the contrast agent has arrived in the region of interest. The system continues to taking fast scan images until the arrival of the bolus of contrast agent has been verified.

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Solon, OH, United States of America

Kecheng Liu