Dual-energy ray imaging methods and systems

Patent metadata

Field	Value
Publication number	US-10339673-B2
Application number	US-201515129455-A
Country	US
Kind code	B2
Filing date	Dec 23, 2015
Priority date	Dec 30, 2014
Publication date	Jul 2, 2019
Grant date	Jul 2, 2019

Abstract

Disclosed is a dual-energy ray imaging method and system. The method comprises: calculating the mass thicknesses of the materials in the overlapped area of two materials by using a calibrated surface fitting method, and then decomposing a pair of original high-energy and low-energy data for this pixel into two high-low-energy data sets corresponding to the two materials, and finally calculating and acquiring the composition result of different materials for each pixel. The disclosure is especially advantageous in that the problem of error recognition of materials due to the two overlapped materials can be eliminated and the stratified imaging of multiple materials can be achieved, thereby improving the accuracy of the substance recognition and reducing the rate of false positive and false negative which is very important to the applications in the field of security check and anti-smuggling.

First claim

We claim:

1. A dual-energy ray imaging method comprising the steps of:
performing a dual-energy transmissive scanning on an object to be inspected to acquire high-energy projection data and low-energy projection data for at least a part of the object to be inspected;
determining whether the high-energy projection data and low-energy projection data correspond to a combination of tow base materials by using a lookup table for single base materials;
for each pixel that is determined to correspond to a combination of the two base materials, searching a high and low energy projection database for mass thicknesses of the two base materials by using the high-energy projection data and the low-energy projection data according to an equation that is determined by using a surface fitting method, the two base materials comprising a first base material and a second base material;
calculating a first high and low energy data set corresponding to the first base material and a second high and low energy data set corresponding to the second base material based on respective mass attenuation coefficients and the mass thicknesses of the two base materials; and
performing a substance recognition by using the first high and low energy data set and second high and low energy data set.

2. The method according to claim 1 , wherein the high-energy projection data and the low-energy projection data are brought into the lookup table of single base materials to determine their positions in high-low-energy curves of single pure materials with different thicknesses, and then to determine whether the positions correspond to the two base materials by calculating distances from the positions to the curves for different base materials.

3. The method according to claim 1 , further comprising steps of:
displaying an image of the object to be inspected based on at least one of the high-energy projection data and the low-energy projection data; and
receiving a user selection of at least part of the image to acquire an area of interest;
wherein the mass thicknesses of the two base materials are calculated with respect to the area of interest.

4. The method according to claim 1 , wherein the high and low energy projection database is created by:
combining step models of first base material and the second base material in an overlapped manner; and
a high-low-energy X-ray DR scan to establish a high-low-energy projection database for two overlapped base materials.

5. The method according to claim 1 , wherein the step of performing the substance recognition comprises using at least one of an R-curve method, a high-low-energy curve method, and an α curve method.

6. The method according to claim 1 , wherein the mass thicknesses of the two base materials are calculated according to quadratic equations:

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Assignees

• Univ Tsinghua
• Nuctech Co Ltd

Inventors

• Li Liang
• Chen Zhiqiang
• Kang Kejun
• Zhang Li
• Zhao Ziran
• Xing Yuxiang
• Xiao Yongshun
• Gu Jianping
• Zheng Juan

Classifications

• G06T2207/10081

  Computed x-ray tomography [CT] · CPC title

• G06T7/0002

  Inspection of images, e.g. flaw detection · CPC title

• G06T2207/30112

  Baggage; Luggage; Suitcase · CPC title

• G06T2211/408

  Dual energy · CPC title

• G06T12/30

  Image post-processing, e.g. metal artefact correction · CPC title