Koninklijke Philips Corporation N.v.

Heike Ruppertshofen

Cristian Lorenz

Jens Wiegert

Peter Prinsen

Roland Proksa

Rafael Wiemker

Tobias Klinder

Holger Schmitt

Sven Kabus

Nicole Schadewaldt

A method for modelling a composition of an object of interest comprises segmenting object of interest image data provided by computer tomography image data resulting in a plurality of image segments. A determined Hounsfield density value is then extracted from the object of interest image data for each image segment. A component ratio of at least two component classes is defined for the object of interest, the at least two component classes having different component Hounsfield density values. At least one component class is assigned to each image segment based on the corresponding determined Hounsfield density value resulting in simulated image segments comprising the component Hounsfield density values. The simulated image segments define simulated image data of the object of interest, where a ratio of the assigned component classes corresponds to the component ratio. A deviation between the simulated image data and the object of interest image data is then determined.

Device and method for modelling a composition of an object of interest

A method for extending initial image data of a subject for dose estimation includes obtaining first image data of the subject for dose calculation, wherein the first image data has a first field of view. The method further includes obtaining second image data for extending the field of view of the first image data. The second image data has a second field of view that is larger than the first field of view. The method further includes extending the first field of view based on the second image data, producing extended image data.

Image data Z-axis coverage extension for tissue dose estimation

The invention relates to a method and an image processing device () for the registration of two images (I, I) that may for example be provided by a CT scanner () and/or an MRI scanner (). According to one embodiment of the invention, the images are first globally registered (GR) with a given registration algorithm using a first parameter vector (p). A user may then select a region of interest ROI, and a plurality of local registrations (LR, . . . LRs, . . . LRn) are calculated for this ROI using the same registration algorithm but different parameter vectors (p, p, . . . p). The results of the local registrations (LR, . . . LRs, . . . LRn) are displayed and the user can select the best local registration(s). In a final step, the selected local registration(s) (LRs) and the global registration (GR) may be merged. Additionally or alternatively, a parameter vector for a local registration in the ROI may be determined by an automatic analysis of the ROI.

Registration of medical images

The invention relates to an apparatus () for calculating an x-ray dose distribution within an object for a computed tomography examination. A primary flux determination unit () determines firstly a primary flux distribution within the object, wherein then this determined primary flux distribution is used as an initial total flux distribution by a total flux determination unit () while applying a six-flux model algorithm. This allows the determination of the total flux distribution to start with a relatively good first approximation of the total flux distribution such that the six-flux model algorithm can determine the total flux distribution very fast. The determined total flux distribution is finally used by a dose distribution determination unit () for determining a total dose distribution. The apparatus allows therefore for a very fast determination of x-ray dose distributions for computed tomography examinations.

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Hamburg, Germany

Heike Ruppertshofen