Koninklijke Philips Corporation N.v.

Manindranath Vembar

Michael Grass

Kevin Martin Brown

Holger Schmitt

Axel Thran

Sven Prevrhal

Hannes Nickisch

Rolf Dieter Bippus

Cristian Buerger

A computing system () includes a computer readable storage medium () with computer executable instructions (), including a biophysical simulator (), and a reference location (), and a processor () configured to the biophysical simulator and simulate a reference FFR value at a predetermined location along a segmented coronary vessel indicated by the reference location. A computer readable storage medium encoded with computer readable instructions, which, when executed by a processor of a computing system, causes the processor to simulate a reference FFR value at a predetermined location along a segmented coronary vessel indicated by a predetermined reference location. A method including simulating a reference FFR value at a predetermined location along a segmented coronary vessel indicated by a predetermined reference location.

Standardized coronary artery disease metric

An imaging system () includes a data acquisition system () configured to produce projection data and at least one memory device with reconstruction algorithms () and at least one blending algorithm (524). The imaging system further includes a reconstructor () configured to reconstruct the projection data with the reconstruction algorithms and generate at least first spectral volumetric image data corresponding to a first basis material content and second spectral volumetric image data corresponding to a second basis material content, and blend the first spectral volumetric image data and the second spectral volumetric image data with the at least one blending algorithm to produce blended volumetric image data.

Material-selective adaptive blending of volumeiric image data

A medical imaging system () includes a masking unit (), an image registration unit (), a motion estimator () and a motion compensating reconstructor (). The masking unit constructs a mask for each reconstructed volumetric phase image of a plurality of reconstructed volumetric phase images that masks portions of a corresponding image external to an anatomical model fitted to a segmented at least one anatomical structure, 5 wherein the plurality of reconstructed volumetric phase images include a target phase and a plurality of temporal neighboring phases reconstructed from projection data. The image registration unit registers the masked reconstructed volumetric phase images. The motion estimator estimates motion between the target phase and the plurality of temporal neighboring phases according to the model based on the registered masked reconstructed 10 volumetric phase images. The motion compensating reconstructor reconstructs a motion compensated medical image from the projection data using the estimated motion of the registered masked reconstructed volumetric phase images.

Model regularized motion compensated medical image reconstruction

A method includes manipulating segmented structure of interest, which is segmented from first reconstructed image data at a reference motion phase of interest, that is registered to second reconstructed image data at one or more other motion phases. The method further includes updating initial motion vector fields corresponding to the registration of the segmented structure of interest to the second reconstructed image data based on the manipulation. The method further includes reconstructing the projection data with a motion compensated reconstruction algorithm employing the updated motion vector fields.

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Twinsburg, OH, United States of America

Manindranath Vembar