Koninklijke Philips Corporation N.V.

Guillaume Rudolf Petrus Thelissen

Filips Van Liere

Johannes Martinus Peeters

Clemens Bos

Shuo Zhang

Disclosed herein is a medical system () comprising a memory () storing machine executable instructions () and an image segmentation algorithm (). The image segmentation algorithm is configured for outputting one or more predetermined anatomical regions within initial magnetic resonance imaging data () descriptive of a predetermined field of view () of a subject (). The medical system further comprises a computational system (), wherein execution of the machine executable instructions causes the computational system to: receive () the initial magnetic resonance imaging data (); receive () the image segmentation comprising the one or more anatomical regions within the magnetic resonance imaging data in response to inputting the initial magnetic resonance imaging data into the image segmentation algorithm; select () at least one of the one or more anatomical regions as a selected image portion () using a predetermined criterion; and reduce () image intensity within the selected image portion to provide intensity corrected magnetic resonance imaging data.

Image intensity correction in magnetic resonance imaging

A magnetic resonance imaging system () includes a data acquisition system () with a main magnet () with an imaging volume. A gradient system (G) generates field gradients (Gx), (Gy) and (Gz). An RF excitation system () generates radio-frequency (RF) excitation pulses. In a receiving mode, an RF coil senses a response, for example in the form of free induction decay signals, including echo signals. An image processor () is arranged to extract thermometry data and longitudinal relaxation time data from the acquired MR signals and to forward corresponding reconstructed images to a display unit ().

Magnetic resonance imaging system, a method of magnetic resonance imaging and a computer program

In a method of visualizing a three-dimensional volume image data set (), a two-dimensional image () is formed by projecting volume image data on a projection plane in that for each pixel () there is determined an intensity value which corresponds to the maximum value or minimum value of the mean intensity along a projection path () through the imaged volume and associated with the relevant pixel. In order to determine the mean intensity, averaging is performed over a plurality of intensity values which neighbor one another along the projection path (). In order to achieve effective noise suppression as well as adequate along image contrast , averaging is performed over at least partly overlapping interval (to) along the projection path (). The method offer the advantage that the user can choose the width of the averaging interval as an additional free parameter, so that image contrast and background noise can be influenced independently.

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Eindhoven, Netherlands

Guillaume Rudolf Petrus Thelissen