Method for iterative image reconstruction for bi-modal CT data

An iterative algorithm, image data technology, applied in 2D image generation, image analysis, image generation and other directions, can solve the problem of not being adopted

Inactive Publication Date: 2013-10-23
SIEMENS AG
View PDF11 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There is also a group of accurate reconstruction methods, but they are currently hardly adopted

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for iterative image reconstruction for bi-modal CT data
  • Method for iterative image reconstruction for bi-modal CT data
  • Method for iterative image reconstruction for bi-modal CT data

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0088] Example 1: Dual Energy Measurement

[0089] The purpose of dual energy measurements is usually to enable material partitioning. For example, iodine and bone can be distinguished in this way. Small noise simplifies the calculation of material decomposition. For this reason, CT images are usually reconstructed with soft convolution kernels, which result in low-noise images. However these smooth images have extremely limited spatial resolution. This leads to an incorrect assignment of image points to substances in some image regions. It is therefore desirable to improve the contrast-to-noise ratio of the image in order to enable error-free substance segmentation.

[0090] Two CT images are presented after the dual source CT measurement and the first image reconstruction, the first with respect to the first tube voltage (eg 80 kV) and the second with respect to the second tube voltage (eg 140 kV). For image PIC A, only the image of the first tube voltage is considered ...

example 2

[0093] Example 2: High-resolution-CT measurement

[0094] CT measurements of standard bores with detector channels are performed, as well as measurements and high-resolution measurements with reduced bores. Such a reduction of the detector aperture makes it possible to obtain spatially high-resolution images. CT images are reconstructed from the two measurements. In contrast to high-resolution measurements in standard measurements, limited positional resolution is present, but a better signal-to-noise ratio because quanta are lost through the reduced aperture.

[0095] Use high resolution measurements for image PIC A and standard measurements for image PIC B. The iterative image reconstruction according to formula (1) results in a high-resolution image with reduced noise.

example 3

[0096] Example 3: Perfusion measurements, especially cardiac perfusion measurements

[0097] After administration of the contrast agent, CT measurement data are acquired at successive times, and a series of temporally successive images, ie images in a plurality of so-called time frames, are reconstructed accordingly. In order to save dose, the measurement is performed with a not too high X-ray intensity. The image thus has noise.

[0098] One of this single image is used as image PIC A; it is temporally high resolution, but has a poor signal-to-noise ratio due to the aforementioned dose savings. As image PIC B, a (possibly weighted) sum is formed from several or all images of the series; this sum image has a high signal-to-noise ratio due to the statistical independence of the individual images. The iterative image reconstruction according to formula (1) results in a temporally high-resolution image with a good signal-to-noise ratio.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention provides a method for iterative image reconstruction for bi-modal CT data. The present invention relates to a method for the reconstruction of image data (PIC) of an examination object from measurement data, wherein the measurement data is acquired in the case of relative rotational movement between a radiation source (C2, C4) of a computed tomography system (C1) and the examination object. First image data (PIC A) with first image characteristic and second image data (PIC B) with second image characteristic, and SNR with the second image characteristic improved relative to the first image characteristic are calculated from the measurement data. The improved image data (PIC) is calculated by using the first image data (PIC A) and the second image data (PIC B) and using an iterative algorithm. In the iterative algorithm, a low pass is applied to a difference between the first image data (PIC A) and image data of an iteration cycle, and a high pass is applied to a difference between the second image data (PIC B) and the image data of the iteration cycle.

Description

technical field [0001] The invention relates to a method for reconstructing image data of an examination object from measurement data which were previously acquired with a relative rotational movement between a radiation source of a computed tomography system and the examination object. Background technique [0002] The tomographic imaging method is characterized in that the internal structure of the examination object can be examined without invasive interventions on the examination object. One possible way of producing a tomographic image consists in recording a plurality of projections from different angles of the object to be examined. From these projections, two-dimensional cross-sectional images or three-dimensional volume images of the object under examination can be calculated. [0003] An example of an imaging method for such tomography is computed tomography. Various methods of scanning an examination object using a CT system are known. For example circular scan...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T11/00G06T17/00
CPCG06T11/006G06T11/003G06T2211/424A61B6/507G06T2211/464G06T7/0012
Inventor H.布鲁德E.克洛茨M.彼得希尔卡R.劳帕克H.肖恩杜比
Owner SIEMENS AG
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap