Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Guenter Lauritsch

Michael Zellerhoff

Dorin Comaniciu

Terrence Chen

Jan Boese

Shanhui Sun

Herbert Bruder

Karl Stierstorfer

Yefeng Zheng

Thomas Redel

Kwok C Tam

Gareth Funka-Lea

Mingqing Chen

Ahmet Tuysuzoglu

Wolfgang Haerer

Yuan Liu

Reconstructing 3-D vessel geometry of a vessel includes: receiving a plurality of 2-D rotational X-ray images of the vessel; extracting vessel centerline points for normal cross sections of each of the plurality of 2-D images; establishing a correspondence of the centerline points from a registration of the centerline points with a computed tomography (CT) 3-D centerline, the registration being an affine or deformable transformation; constructing a 3-D centerline vessel tree skeleton of the vessel from the centerline points of the 2-D images; constructing an initial 3-D vessel surface having a uniform radius normal to the 3-D centerline vessel tree skeleton; defining sample points based sampling on median radii to the 3-D centerline vessel tree skeleton of the initial 3-D vessel surface; and constructing a target 3-D vessel surface by deforming the initial vessel surface using the sample points to provide a reconstructed 3-D vessel geometry of the vessel.

3-D vessel tree surface reconstruction

A method and system for estimating 3D cardiac motion from a single C-arm angiography scan is disclosed. An initial 3D volume is reconstructed from a plurality of 2D projection images acquired in a single C-arm scan. A static mesh is extracted by segmenting an object in the initial 3D volume. The static mesh is projected to each of the 2D projection images. A cardiac phase is determined for each of the 2D projection images. A deformed mesh is generated for each of a plurality of cardiac phases based on a 2D contour of the object and the projected mesh in each of the 2D projection images of that cardiac phase.

Method and system for 3D cardiac motion estimation from single scan of C-arm angiography

A system and method of obtaining perfusion data for cerebral tissue is described. The system includes a C-arm X-ray device and a computing system configured to obtain sets of rotational projection X-ray data suitable for reconstructing 3D voxel data sets. A first data set is obtained of the patient, and then contrast material is injected into the vascular system to obtain a second 1 data set. A first voxel data set is subtracted from the second voxel data set, and the resultant data set is processed so as to segment the contrast-enhanced vasculature from the remaining data. The segmented voxels are subtracted from the resultant voxel data set, so as to yield a functional data set representing the difference between the attenuation of the tissues after administering contrast agent and the tissues prior to administering the contrast agent, without the contrast enhanced vasculature. The attenuation of the functional data set represents the perfusion or cerebral blood volume (CBV).

Measuring blood volume with C-arm computed tomography

An imaging method is disclosed for a multi-slice spiral CT scan. A CT unit is disclosed for carrying out this method. In the method, the filtering may be formed by use of multiple applications of a ramp filter and a masking operation to a projection image in a different sequence. The CT unit may include, for filtering purposes, multiple applications of a ramp filter and a masking operation to a projection image in a different sequence.

Imaging method for a multi-slice spiral CT scan, and a computer tomography unit for carrying out this method

In a method for reconstruction of a three-dimensional image of an object scanned in linear or circular fashion in the context of a tomosynthesis. The object is transirradiated with X-rays from various projection angles &phgr; for the recording of the projection images, and the radiation exiting from the object is recorded by a detector that supplies digital output image signals. The output image signals representing the projection image data are supplied to a computer for image reconstruction. In the context of the reconstruction a filter is first produced, on the basis of the following steps: A 3D transmission function H (&ohgr; ,&ohgr; ,&ohgr; ) is calculated from the recording geometry for the individual projection image recording and the back-projection of the individual projection images into the 3D reconstruction image volume. By approximation, the 3D transmission function H (&ohgr; ,&ohgr; ,&ohgr; ) is inverted for the determination of an inversion function H (&ohgr; ,&ohgr; ,&ohgr; ). A 3D filtering function H (&ohgr; ,&ohgr; ,&ohgr; ) is produced dependent on one or more desired image characteristics of the reconstruction image. A resulting 3D filtering function H (&ohgr; ,&ohgr; ,&ohgr; ) is determined by multiplication of the 3D filtering function H (&ohgr; ,&ohgr; ,&ohgr; ) and the inversion function H (&ohgr; ,&ohgr; ,&ohgr; ). A 2D filtering function H (&ohgr; ,&ohgr; ) is determined from the resulting 3D filtering function H (&ohgr; ,&ohgr; &ohgr; ) by coordinate transformation of the 3D object space into the 2D projection image space of the respective individual projection images at the projection angle &phgr;. After calculating the filter, the reconstruction of the image takes place in the computer by application of the 2D filtering function H (&ohgr; ,&ohgr; ) to the associated individual projection image data, and production of the reconstruction image by back-projection of the filtered individual projection image data, into the 3D reconstruction image volume.

Method for reconstructing a three-dimensional image of an object scanned in the context of a tomosynthesis, and apparatus for tomosynthesis

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Nürnberg, Germany

Guenter Lauritsch