Koninklijke Philips Corporation N.v.

Technische Universitat Munchen

Peter Noel

Thomas Koehler

Roland Proksa

Hanns-Ingo Maack

Bernhard Johannes Brendel

Heiner Daerr

Franz Pfeiffer

Andriy Yaroshenko

Daniela Muenzel

Maximilian Von Teuffenbach

Lukas Benedict Gromann

Fabio De Marco

Willer Konstantin

Konstantin Willer

Julia Herzen

Alexander Fingerle

The invention relates to beam hardening correction in X-ray Dark-Field imaging of a subject including a first material and a second material, the first and second material having different beam hardening properties. As the X-ray imaging data includes information on the internal structure of the imaged subject, such information may be used, together with appropriate calibration data to identify the beam hardening contributions occurring in the imaged area of the subject, so to allow for a correction of artifacts due to beam hardening in X-ray Dark-Field imaging.

Beam hardening correction in x-ray dark-field imaging

A system and related method for signal processing. Interferometric projection data reconstructed into one or more images for a spatial distribution of a physical property of an imaged object. The interferometric projection data is derived from signals acquired by an X-ray detector (D), said signals caused by X-ray radiation after interaction of said X-ray radiation with an interferometer and with the object (OB) to be imaged, said interferometer (IF) having a reference phase. A reconstructor (RECON) reconstructs for the image(s) by fitting said data to a signal model by adapting fitting variables, said fitting variables including i) one or more imaging variables for the one or more images and ii), in addition to said one or more imaging variables, a dedicated phase variable for a fluctuation of said reference phase.

Robust reconstruction for dark-field and phase contrast CT

The invention relates to a method of Computed Tomography imaging comprising: a. Performing a single acquisition of image data from at least two contrast agents into a blood vessel network, a first contrast agent among said at least two contrast agents having been in said blood vessel network for a longer time than a second contrast agent among said at least two contrast agents, b. Processing said image data using K-Edge detection and/or iodine delineation to separate data associated with each contrast agents in order to obtain a concentration map of each contrast agent, c. Determining from said image data a first part of the blood vessel network comprising both the first contrast agent and the second contrast agent, and a second part of the blood vessel network comprising only the first contrast agent, d. Calculating a partial blood volume map of the first part of the blood vessel network based on the total amount of second contrast agent and on the concentration map of the second contrast agent, e. Calculating a partial blood volume map of the second part of the blood vessel network based on the total amount of first contrast agent, on the concentration map of the first contrast agent and on the partial blood volume map of the first part of the blood vessel network.

Method of computed tomography imaging

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Eindhoven, Netherlands

Peter Noel