Koninklijke Philips Corporation N.V.

Husqvarna Ab

Ming Yang

Feng Huang

Jeffrey C Hickman

Ni Zugen

David Lawrence Estey

Garrett Sherman

Chad Jones

Li Li

Chenguang Zhao

Yu Li Huang

A blower () includes a blower attachment housing (), a power head housing () having a handle () operably coupled thereto, a motor () disposed in the power head housing (), a fan () disposed in the blower attachment housing (), a battery (), and an intake chamber () disposed between the motor () and the fan () to enable the air to enter the blower () between the motor () and the fan ().

Blower with improved balance and construction

Embodiments of the present invention provide a method for generating a synthetic diffusion image. The method comprises the steps of acquiring multiple sets of initial diffusion scan data by means of diffusion weighted magnetic resonance scans at multiple initial b-values, deriving an initial diffusion image from at least part of the initial diffusion scan data, acquiring target diffusion scan data by means of a diffusion weighted magnetic resonance scan at a target b-value higher than each of the initial b-values, and generating the synthetic diffusion image by performing a cost function based reconstruction to apply a fidelity term in k space to the synthetic diffusion image based on at least the initial diffusional image, and the target diffusion scan data.

Diffusion MRI method for generating a synthetic diffusion image at a high B-value

The invention provides a device for producing a magnetic resonance image. The device comprises a collecting unit adapted for collecting k space samples that are located on a non-Cartesian grid in a non-Cartesian coordinate space or non-uniformly located on a Cartesian grid in a Cartesian coordinate space, the non-Cartesian/Cartesian coordinate space adapted to be decomposed into a plurality of subspaces, each of which extends along one or more coordinate axes of the non-Cartesian/Cartesian coordinate space; a weight calculation unit () adapted for calculating a decomposed sample density weight function of the k space samples in each individual subspace and determining a density weight function in the non-Cartesian/Cartesian coordinate space via a multiplication of the decomposed sample density weight functions of the k space samples in the plurality of subspaces; a gridding unit adapted for interpolating the k space samples in the non-Cartesian/Cartesian coordinate space onto a uniform Cartesian grid in a k space based on the density weight function of the k space samples in the non-Cartesian/Cartesian coordinate space; and a reconstructing unit adapted for reconstructing the magnetic resonance image based on the interpolated k space samples. By means of the invention, fast, preferably on-demand, calculation of the sampling density weights may be achieved.

MRI with variable density sampling

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Suzhou, China

Ming Yang