Abstract: A spectral CT image reconstructing method includes: collecting incomplete original projection data in each of a plurality of energy windows; performing a projection data cross estimation using corresponding original projection data in at least one pair of energy windows constituted by different energy windows of the plurality of energy windows to obtain estimated projection data, wherein each pair of energy windows comprises a first energy window and a second energy window; combining the original projection data and the corresponding estimated projection data to obtain complete projection data; and reconstructing a spectral CT image using the complete projection data.

Abstract: The present disclosure provides a decomposition method based on basis material combination. In the present disclosure, a scanned object is divided into a plurality of regions, the basis material combinations used in each of the divided regions are different each other, and the scanned object is re-divided according to the re-determined equivalent atomic number of its each point until the change on decomposition coefficient meets certain conditions. Thereby, a decomposition method based on dynamic basis material combinations is realized, which reduces a decomposition error caused by improper selection of the basis material combination and improves the accuracy of the decomposition and substance identification of the multi-energy CT.

Abstract: The present disclosure discloses a method, an apparatus and a system for reconstructing an image of a three-dimensional surface.

Abstract: An image processing method, comprising: acquiring, by a CT scanning system, projection data of an object; and processing, by using a convolutional neural network, the projection data, to acquire an estimated image of the object. The convolutional neural network comprises: a projection domain network for processing input projection data to obtain estimated projection data; an analytical reconstruction network layer for performing analytical reconstruction to obtain a reconstructed image; an image domain network for processing the reconstructed image to obtain an estimated image, a projection layer for performing a projection operation by using a system projection matrix of the CT scanning system, to obtain a projection result of the estimated image; and a statistical model layer for determining consistency among the input projection data, the estimated projection data, and the projection result of the estimated image based on a statistical model.

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.

Abstract: The present disclosure provides a decomposition method based on basis material combination. In the present disclosure, a scanned object is divided into a plurality of regions, the basis material combinations used in each of the divided regions are different each other, and the scanned object is re-divided according to the re-determined equivalent atomic number of its each point until the change on decomposition coefficient meets certain conditions. Thereby, a decomposition method based on dynamic basis material combinations is realized, which reduces a decomposition error caused by improper selection of the basis material combination and improves the accuracy of the decomposition and substance identification of the multi-energy CT.

Abstract: Methods and system for decomposing a high-energy dual-energy X-ray CT material are disclosed. In the method, two types of effect such as Compton effect and electron pairing effect which dominates are reserved and the influence of the other effect such a photoelectric effect is removed so as to improve the accuracy of the material decomposition. The unique advantage of the present disclosure is to effectively remove the error of the calculated atomic number Z due to directly selecting two effects during processes of material decomposition in the conventional dual-energy CT method. This may greatly improve the accuracy of dual-energy CT identification of the material, and it is important to improve the conventional dual-use CT imaging system applications, such as clinical therapy, security inspection, industrial non-destructive testing, customs anti-smuggling and other fields.

Abstract: The disclosure provides a scanning imaging system for security inspection of an object and an imaging method thereof, the system comprising: a conveying unit configured for bringing the object to move along a conveying direction; a plurality of radiographic sources at one side of the conveying unit, being arranged successively in a direction vertical to a plane, in which the conveying unit is located, and configured for alternately emitting ray beams to form a scanning area; a linear detector array at the other side of the conveying unit, being configured for detecting first projection images, which are formed after the ray beams emitted by the plurality of radiographic sources penetrate through the object, in the process of the object passing through the scanning area; an imaging unit configured for obtaining a first reconstructed image of the object based on the first projection images of the plurality of radiographic sources.

Abstract: An X-ray detection method and an X-ray detector are provided. The X-ray detection method according to embodiments of the present disclosure includes: dividing an energy range of photons emitted by an X-ray source into a number N of energy windows, where N is an integer greater than 0; obtaining a weighting factor for each of the number N of energy windows based on linear attenuation coefficients of a substance of interest and a background substance of an imaging target; obtaining a weighting factor matrix for M output channels of an X-ray detector based on the weighting factor for each of the number N of energy windows, where M is an integer greater than 0; and obtaining output results of the M output channels based on the weighting factor matrix and numbers of photons having an energy range falling into individual energy windows of the number N of energy windows.

Abstract: The present disclosure discloses a ray transmission and fluorescence CT imaging system and method. The system comprises: a ray source configured to emit a beam of rays; a rotational scanning device configured to perform rotational CT scanning on an object to be inspected; a transmission CT detector configured to receive the beam of rays which has passed through the object; a fluorescence CT detector configured to receive fluorescent photons excited by irradiation of the beam of rays on the object; a data acquisition unit configured to acquire a transmission data signal and a fluorescence data signal respectively; and a control and data processing unit configured to control the ray source to emit the beam of rays, control the rotational scanning device to perform the rotational CT scanning, and obtain a transmission CT image and a fluorescence CT image simultaneously based on the transmission data signal and the fluorescence data signal.

Abstract: A method and device for reconstructing a CT image and a storage medium are disclosed. CT scanning is performed on an object to be inspected to obtain projection data. The projection data is processed using a first convolutional neural network to obtain processed projection data. The first convolutional neural network comprises a plurality of convolutional layers. A back-projection operation is performed on the processed projection data to obtain a reconstructed image.

Abstract: A method and device for reconstructing a CT image and a storage medium are disclosed. CT scanning is performed on an object to be inspected to obtain projection data on a first scale. Projection data on a plurality of other scales is generated from the projection data on the first scale. Projection data on each scale is processed on the corresponding scale by using a first convolutional neural network to obtain processed projection data, and a back-projection operation is performed on the processed projection data to obtain a CT image on the corresponding scale. CT images on the plurality of scales are fused to obtain a reconstructed image of the object to be inspected.

Abstract: The present disclosure provides a low-angle self-swinging type computed tomography (CT) apparatus, which is provided with an X-ray accelerator and a plurality of rows of detectors and is configured to include a slip ring, such that the slip ring with the accelerator and the detectors thereon is capable of performing a single-pendulum reciprocating movement while an objected to be inspected passes through the slip ring, a three dimension CT image of the object is displayed, thereby achieving accurate inspection for large-scale objects, such as van containers.

Abstract: A spectral CT image reconstructing method includes: collecting incomplete original projection data in each of a plurality of energy windows; performing a projection data cross estimation using corresponding original projection data in at least one pair of energy windows constituted by different energy windows of the plurality of energy windows to obtain estimated projection data, wherein each pair of energy windows comprises a first energy window and a second energy window; combining the original projection data and the corresponding estimated projection data to obtain complete projection data; and reconstructing a spectral CT image using the complete projection data.

Abstract: A method and apparatus for reconstructing an incident energy spectrum for a detector are disclosed. In this method, an object to be inspected is illuminated with rays, and then rays transmitted through the object to be inspected are received by the detector to convert the received rays into data of a detected energy spectrum. The incident energy spectrum for the detector is reconstructed based on the data of the energy spectrum using a statistical iterative algorithm with a pre-established detector response function. With the above solution of the embodiments, the incident energy spectrum for the detector can be more accurately acquired, thereby reducing a distortion of the incident energy spectrum caused by the detector.

Abstract: Methods and system for decomposing a high-energy dual-energy X-ray CT material are disclosed. In the method, two types of effect such as Compton effect and electron pairing effect which dominates are reserved and the influence of the other effect such a photoelectric effect is removed so as to improve the accuracy of the material decomposition. The unique advantage of the present disclosure is to effectively remove the error of the calculated atomic number Z due to directly selecting two effects during processes of material decomposition in the conventional dual-energy CT method. This may greatly improve the accuracy of dual-energy CT identification of the material, and it is important to improve the conventional dual-use CT imaging system applications, such as clinical therapy, security inspection, industrial non-destructive testing, customs anti-smuggling and other fields.

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.

Abstract: Disclosed is a CT imaging method and system. The method includes: CT scanning an object with a dual-energy CT system to obtain a first complete set of projection data in a first scan mode, and to obtain a second incomplete set of projection data in a second scan mode; reconstructing a first attenuation coefficient image of the object from the first set of projection data, and extracting, from the first attenuation coefficient image, prior structure information of the object indicating edge intensity; and reconstructing a second attenuation coefficient image of the object from the second incomplete set of projection data using the extracted prior structure information as a constraint. With the method using the prior structure information of the imaged object as a constraint in reconstruction, it is possible to dramatically reduce an amount of data required for reconstruction, and achieve satisfactory effects even with ill-conditioned problems of limited-angle and inner reconstruction.

Abstract: The present disclosure relates to a self-prior information based X-ray dual-energy CT reconstruction method, which can utilize information inherent in data to provide a prior model, thereby obtaining a reconstructed image with a high quality. The X-ray dual-energy CT reconstruction method according to the present disclosure comprises: (a) rating an energy spectrum and establishing a dual-energy lookup table; (b) collecting high-energy data pH and low-energy data pL of a dual-energy CT imaging system using a detector of the dual-energy CT imaging system; (c) obtaining projection images R1 and R2 of scaled images r1 and r2 according to the obtained high-energy data pH and low-energy data pL; (d) reconstructing the scaled image r2 using a first piece-wise smooth constraint condition and thereby obtaining an electron density image; and (e) reconstructing the scaled image r1 using a second piece-wise smooth constraint condition and thereby obtaining an equivalent atomic number image.

Abstract: CT imaging systems and methods thereof are disclosed. A common CT scanning is performed on an object to obtain a common CT imaging. An area of interest is determined from the image. A CT scanning is performed on the area of interest under a plurality of energy windows by a photon counter detector. A high resolution image of the area of interest is reconstructed. The discrimination of energy spectrum is higher and the result so obtained is more stable by using a photon counter detector to collect photon count projection data of a plurality of energy windows and thus it may be decomposed into a plurality of basis functions.