Koninklijke Philips Corporation N.v.

Michael Helle

Heinrich Schulz

Steffen Renisch

Nicole Schadewaldt

Christian Stehning

Steffen Weiss

Tim Nielsen

Ulrich Wolfgang Katscher

Thomas Lindner

A magnetic resonance imaging system () for acquiring magnetic resonance data () from an imaging zone () includes a memory () for storing machine executable instructions () and pulse sequence commands (). The pulse sequence commands cause the magnetic resonance imaging system to provide at least one spatially selective saturation pulse () to at least one selected volume (') that is at least partially outside of a region of interest () and within the imaging zone. The magnetic resonance imaging system performs a non-selective inversion () of spins in the region of interest followed by a readout () of the magnetic resonance data which is reconstructed () into an image ().

Imaging fluid flow into a region of interest

It is an object of the invention to improve tissue classification in MRI images. In particular it is an object of the invention to improve the classification of bone and air in MRI images. This object is achieved by a method for tissue classification in a region of interest in a magnetic resonance (MR) image comprising a first region and a second region, wherein the first region represents air and the second region represents bone. The method comprises the steps of: &#x2014;acquiring a first magnetic resonance image comprising the first and the second region and; &#x2014;acquiring a second magnetic resonance image comprising the first and the second region, wherein the first region has a different shape in the second magnetic resonance image compared to the first magnetic resonance image and; &#x2014;identifying the first region and second region in the first and second image and; &#x2014;comparing the first image and the second image with respect to the first region and the second region and; &#x2014;classifying the first region as region representing air based on a presence of a shape difference between the first and the second image and classifying the second region as bone based on an absence of the shape difference between the first and second image.

Method for tissue classification, computer program product and magnetic resonance imaging system

A magnetic resonance imaging (MRI) system () that generates information indicative of a fluid flow in accordance with a pseudo-continuous arterial spin labeling (pCASL) method. The MRI system may include at least one controller () configured to generate a pseudo-continuous arterial spin labeling (pCASL) pulse sequence () including at least a first gradient (GR) pulse sequence () having a sinusoidal waveform including a plurality of cycles, and a second radio frequency (RF) pulse sequence () including a half-wave rectified sinusoidal waveform having a plurality of cycles and which is synchronous with the first GR pulse sequence; label at least part of the fluid flow in a labeling region during a labeling mode using the pCASL pulse sequence; acquire label and control image information of the fluid flow at an imaging region proximal to downstream of the labeling region; and/or generate image information in accordance with a difference of the acquired label and control image information. The sinusoidal gradient waveform results in less acoustic noise during execution of the pulse sequence.

Arterial spin labeling with reduced acoustic noise emissions and method of operation thereof

A medical apparatus () includes a magnetic resonance imaging system () for acquiring magnetic resonance data () from an imaging zone (); a processor () for controlling the medical apparatus; a memory () storing machine executable instructions (). Execution of the instructions causes the processor to: acquire () the magnetic resonance data using a pulse sequence () which specifies an echo time greater than 400 &#x3bc;s; reconstruct () a magnetic resonance image using the magnetic resonance data; generate () a thresholded image () by thresholding the magnetic resonance image to emphasize bone structures and suppressing tissue structures in the magnetic resonance image; and generate () a bone-enhanced image by applying a background removal algorithm to the thresholded image.

Detection of bone tissue using magnetic resonance imaging

A pseudo CT Hounsfield Unit value for a volume element within a subject is estimated from a plurality of magnetic resonance images having different contrasts. The method includes determining a relative prevalence of a first tissue class and second tissue class within the volume element from a first magnetic resonance image and a second magnetic resonance image, respectively. Then a relative prevalence of a third tissue class is determined within the volume element based on substraction of a relative prevalence of the first and/or second tissue class from a total tissue prevalence. A reference Hounsfield Unit value is provided for the first, second and third tissue class. Finally, a pseudo Housfield value is estimated for the volume element by determining a weighted sum of the first, second and third reference Hounsfield unit value, with weight factors which are based on the determined relative prevalences of the first, second and third tissue class.

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Eindhoven, Netherlands

Michael Helle