US 2010/0246751 A1 · METHOD AND IMAGE RECONSTRUCTION DEVICE FOR RECONSTRUCTING IMAGE DATA

Abstract

A method and an image reconstruction device are disclosed for reconstructing image data on the basis of input projection data obtained via an X-ray computerized tomography system. A target convolutional kernel is selected, which, when reconstructing image data from the input projection data using simple filtered back projection, would lead to target image characteristics. Image data is then reconstructed using an iterative reconstruction method of at least one embodiment. In at least one embodiment, the method includes a) reconstructing image data of a first iterative stage from the input projection data, b) generating synthetic projection data on the basis of the image data of the current iterative stage, c) forming difference projection data on the basis of the input projection data and the synthetic projection data, d) generating residue image data from the difference projection data, e) combining the residue image data with the image data of the current iterative stage to form image data of an additional iterative stage, wherein the image data of the current iterative stage is subjected to filtering before or during combination with the residue image data by using a regularization convolutional kernel which is determined on the basis of the selected target convolutional kernel, and f) repeating b) to e) until a termination condition occurs.

Claims19

Dependent claims

A method for reconstructing image data on the basis of input projection data obtained via an X-ray computerized tomography system, wherein a target convolutional kernel is selected, which, when reconstructing image data from the input projection data using simple filtered back projection, would lead to target image characteristics, and wherein image data are then reconstructed using an iterative reconstruction method comprising:

reconstructing image data of a first iterative stage from the input projection data;
generating synthetic projection data on the basis of the image data of a current iterative stage;
forming difference projection data on the basis of the input projection data and the synthetic projection data;
generating residue image data from the difference projection data;
combining the residue image data with the image data of the current iterative stage to form image data of an additional iterative stage, wherein the image data of the current iterative stage is subjected to filtering before or during combination with the residue image data by using a regularization convolutional kernel which is determined on the basis of the selected target convolutional kernel;
and
repeating the generating synthetic projection data, forming difference projection data, generating residue image data and combining until a termination condition occurs.

4 more elements

An image reconstruction device for reconstructing image data of an object, comprising:

a projection data interface to accept input projection data obtained via an X-ray computerized tomography system;
a target convolutional kernel selection unit to select a target convolutional kernel, which, when reconstructing image data from the input projection data using simple filtered back projection, would lead to certain image characteristics;
and
an iterative reconstruction unit, adapted to reconstruct image data based on the input projection data using an iterative reconstruction method, comprising:
reconstructing image data of a first iterative stage from the input projection data,
generating synthetic projection data on the basis of the image data of a current iterative stage,
forming difference projection data on the basis of the input projection data and the synthetic projection data,
generating residue image data from the difference projection data,
combining the residue image data with the image data of the current iterative stage to form image data of an additional iterative stage, wherein the image data of the current iterative stage is subjected to filtering before or during combination with the residue image data by using a regularization convolutional kernel determined on the basis of the selected target convolutional kernel, and
repeating the generating synthetic projection data, forming difference projection data, generating residue image data and combining until a termination condition occurs;
and
an image data interface to output the reconstructed image data.

9 more elements

Dependencies are inferred from the claim text.

Method and image reconstruction device for reconstructing image data

Life of this patent

Method and image reconstruction device for reconstructing image data

Life of this patent

Abstract

Claims19