Koninklijke Philips Corporation N.v.

U.S. Philips Corporation

Arianne M C Van Muiswinkel

Ronaldus F J Holthuizen

Johan Samuel Van Den Brink

Johannes Petrus Groen

Thomas Jaermann

Frank G D Hoogenraad

Gerald Van Ensbergen

An imaging method for imaging a subject () including fibrous/anisotropic structures () includes acquiring three-dimensional image representations without and with a plurality of different diffusion weighting and directions. When a user () hovers a selection device over a voxel of the image, a fiber representation () is extracted in substantially real time. The representation is generated by following a direction of a major eigenvector efrom voxel to voxel. A human-viewable display of the fiber representation is produced ().

Sweeping real-time single point fiber

An imaging method ( ) for imaging a subject ( ) including fibrous or anisotropic structures ( ) includes acquiring a three-dimensional apparent diffusion tensor map ( ) of a region with some anisotropic structures ( ). The apparent diffusion tensor at a voxel is processed ( ) to obtain eigenvectors (e , e , e ) and eigenvalues (&lgr; , &lgr; , &lgr; ). A three-dimensional fiber representation ( ) is extracted ( ) using the eigenvectors and eigenvalues. During the extracting ( ), voxels are locally interpolated ( ) in at least a selected dimension in a vicinity of the fiber representation ( ). The interpolating includes weighting the voxels by a parameter indicative of a local anisotropy. The interpolating results in a three-dimensional fiber representation ( ) having a higher tracking accuracy and representation resolution than the acquired tensor map ( ).

Diffusion tensor magnetic resonance imaging including local weighted interpolation

An imaging sequence, which generates a static image data set and a plurality of differently diffusion-weighted data sets, is repeated and the data sets stored in memories ( ). Each data set is reconstructed into corresponding images stored in sub memories ( ). The images are compared macroscopically ( ) and shifted ( ) into optimal alignment. Local regions of the images are analyzed ( ) and adjusted ( ) for better conformity. The static images and like spatially encoded images are compared with each other and those outside a preselected similarity threshold are rejected ( ). The remaining like images are combined ( ) and subject to a diffusion analysis ( ) to generate an image of an anisotropic structure in the imaging region. The anisotropic structure and other image information are displayed on a monitor ( ).

Retrospective selection and various types of image alignment to improve DTI SNR

An imaging method for imaging a subject ( ) including anisotropic or fibrous structures ( ) includes acquiring a three-dimensional apparent diffusion tensor map ( ) of a region with some anisotropic structures ( ). The apparent diffusion tensor map ( ) is processed to obtain ordered eigenvectors and eigenvalues ( ) of diffusion tensor map voxels. A three-dimensional fiber representation ( ) is tracked using the eigenvectors and eigenvalues ( ). The three-dimensional fiber representation ( ) is rendered as a hyperstreamline representation ( ). An background image representation ( ) is generated. A human-viewable display ( ) is produced including the rendered hyperstreamline representation ( ) superimposed on the generated image background representation ( ).

Diffusion tensor magnetic resonance imaging including fiber rendering using hyperstreamlines

The invention relates to a method of deriving time-averaged moments of a convolution profile from dynamic input and arrival profiles. A convolutive relation exists between the arrival profile and the input profile. According to the invention the time-averaged moment of the convolution profile is calculated from time-averaged moments of the dynamic input and arrival profiles. The method is used notably for the study of perfusion effects by means of magnetic resonance imaging.

Deriving time-averaged moments

The invention relates to a magnetic resonance imaging method. The method includes the execution of image pulse sequences for the measurement of magnetic resonance image signals and navigator signals. After the execution of the image pulse sequence, the navigator MR signal is checked so as to determine whether the navigator MR signal meets a predetermined quality criterion. If the navigator MR signal does not meet the quality criterion, the navigator MR signal and the magnetic resonance imaging signals corresponding to the navigator MR signal are measured again.

Magnetic resonance method and device

According to the known method, a reference measurement is performed by measurement of magnetic resonance signals, without application of a magnetic gradient field to introduce phase encoding in the magnetic resonance signals. According to the invention, two measurements are performed with a read-out gradient of opposite polarity at substantially corresponding instants, relative to an instant at which the contributions to the phase error due to frequency deviations are zero. The advantage of the novel method resides in the fact that a higher insensitivity to field inhomogeneities and chemical shifts is achieved.

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Best, Netherlands

Arianne M C Van Muiswinkel