16 results about "Effective atomic number" patented technology

The invention relates to the technical field of X-ray detection, and discloses an X-ray detection method and detector for detecting various densities and materials, and the method comprises the steps: carrying out the penetration imaging of an X-ray beam through a double-layer TFT detector structure; forming a first common energy X-ray image on the first TFT imaging layer for X-rays penetrating through the detected object, and forming a first high-energy X-ray image filtered by the copper filter layer on the second TFT imaging layer; performing preprocessing to obtain a second ordinary energy X-ray image and a second high-energy X-ray image; performing dual-energy-domain feature extraction, and constructing an effective atomic number map and a material density map; and executing feature space clustering analysis and decision tree classification, and outputting a final detection result. According to the invention, the image information of different energy domains is effectively integrated, the recognition capability of a mixed material and a complex structure is enhanced, the service life of a TFT detector is prolonged, and the system operation cost is reduced.

A method is provided for generating a medical image indicating the presence of uric acid. A base image indicates the presence of uric acid on a pixel-by-pixel basis. Pixel values of the base image are modified using the effective atomic number and the electron density values associated for the tissue associated with those pixels.

This disclosure relates to an intelligent analysis method and system for the composition of urinary tract stones, belonging to the field of urinary tract stone composition analysis technology. The intelligent analysis method for urinary tract stone composition, applied to stone type identification, includes: acquiring an atomic number image of urinary tract stones corresponding to a dual-energy abdominal image; extracting multiple component percentages from multiple bar charts corresponding to the effective atomic numbers in the atomic number image of the urinary tract stones, and identifying the stone type corresponding to the dual-energy abdominal image based on the multiple component percentages corresponding to the multiple bar charts and multiple preset stone type component percentage intervals. Embodiments of this disclosure can achieve intelligent identification of stone types.

Provided are an image processing device, a method, a program product, and a recording medium capable of analyzing a tissue of interest for each component. An image processing device that processes an image obtained by an X-ray computed tomography device capable of measuring an effective atomic number is provided with a processor. The processor performs: a process for displaying, on the display unit, at least one of a plurality of images obtained by the X-ray computed tomography device; accepting setting of a first area on the image displayed on the display unit; accepting setting of an effective atomic number as an analysis object; extracting pixels including the effective atomic number component in the first region, and extracting a second region including the effective atomic number component in the first region; determining the shape of the second region; and displaying the shape of the second region on a display unit.

This disclosure provides a rock type identification method, device, and storage medium, belonging to the field of oil and gas exploration technology. The method comprises: obtaining a first image and a second image obtained by scanning a rock sample using X-rays of different energy values; obtaining a characteristic curve of the rock sample based on the first and second images; wherein the characteristic curve includes a density curve and / or an effective atomic number curve; and determining the target type of the rock sample based on the characteristic curve. Embodiments of this disclosure enable rapid and accurate rock sample type identification.

Provided is an object detection method and system capable of increasing a detection rate for hazardous substances such as liquid explosives as well as existing explosives, the object detection method including (a) preparing an X-ray image of a subject, (b) calculating effective atomic number values (Zeff) by using the X-ray image, and (c) segmenting a target object image from the X-ray image by using the effective atomic number values and energy-band-based multi-energy image reconstruction.

The application discloses a kind of geological sample component identification and abnormal detection system based on machine learning, it is related to geological sample component identification and detection technical field, first by the ratio of Compton and Rayleigh scattering intensity calculated by ray fluorescence energy spectrum, obtain effective atomic number and its uncertainty;Again, the continuum of short-wave infrared spectrum is removed, the depth of aluminum hydroxyl absorption band and band shape asymmetry are extracted, and the slope is used to represent the granularity, and the monotone spline is trained to obtain the clay proportion estimation;According to the end member set and atomic number table, the theoretical atomic number and uncertainty are obtained, and the measurement side is integrated into a unified scale to obtain the cross-modal inconsistency index.The state variable and the index are used as the target to adaptively optimize the collection and retest, and the consistency constraint is executed to solve the mixture and abnormality determination.The application can carry out high-precision identification and abnormality determination under complex working conditions.

The invention provides a Bi-based material for X-ray detection and protection and a preparation method and application thereof, and belongs to the technical field of X-ray detection and protection. According to the invention, the Bi-based material is BiO (IO3), BiVO4 or Bi2WO6; the preparation method comprises the following steps: mixing an I2O5 solution and a BiH10N3O14 suspension, and reacting to obtain BiO (IO3); the preparation method comprises the following steps: mixing Bi (NO3) 3.5 H2O, NH4VO3 and a nitric acid solution, and dropwise adding ammonia water into the mixed solution until yellow precipitate appears, so as to obtain BiVO4; the preparation method comprises the following steps: mixing a Na2WO4. 2H2O solution and a Bi (NO3). 5H2O suspension, and reacting to obtain Bi2WO6. The Bi-based material disclosed by the invention has excellent X-ray detection performance and protection effect, and due to the extremely high atomic number of the Bi element, the high equivalent atomic number and density of the material are finally formed, so that full absorption of X-rays is realized.

The present application provides a kind of material identification method, this method is based on the material decomposition of double effect, is calibrated with two or more materials, improves the accuracy of material decomposition, obtains more accurate atomic number estimation physical model by adaptive parameter determination method.The present application is divided into empirical double effect material decomposition and adaptive effective atomic number estimation two parts, wherein empirical double effect material decomposition, by the calibration of multiple standard phantoms, the determination of decomposition parameters and the estimation of electron density are realized by the polynomial combination of projection data and the constraint in image domain;Effective atomic number estimation establishes an adaptive effective atomic number estimation model by the calibration of known standard phantom, realizes the estimation of effective atomic number of imaging material.The present application can realize more accurate electron density and effective atomic number estimation for different kinds of materials at different energies through adaptive material decomposition algorithm, improves the precision of material identification.

This invention discloses a material identification method and system based on physical constraint deep learning. The steps of this invention include: constructing a simulation phantom and assigning it material information; acquiring projection data of the simulation phantom; generating high- and low-energy reconstructed images based on the projection data, using the effective atomic number image and density image of the simulation phantom as basic label images; generating reconstructed images at a set energy based on the projection data as single-energy label images; inputting the basic label images into an X-ray dynamic interaction model, outputting single-energy images to optimize the X-ray dynamic interaction model, obtaining an MLP-type X-ray dynamic interaction model; inputting the high- and low-energy reconstructed images into the main network model to obtain effective atomic number images and density images, and inputting them into the MLP-type X-ray dynamic interaction model to generate a single-energy image optimized main network model; inputting the reconstructed image of the object to be detected into the main network model to obtain its effective atomic number image and density image.

The present invention provides a liquid identification method based on multimodal fusion images of a security inspection X-ray machine. The method comprises: scanning a container containing a liquid to be inspected to obtain a high-energy X-ray image, a low-energy X-ray image, and a pseudo-color X-ray image; determining a first-type cross region corresponding to the container in the pseudo-color X-ray image; determining an effective atomic number image based on the high-energy X-ray image and the low-energy X-ray image; determining a second-type cross region in the high-energy X-ray image, a third-type cross region in the low-energy X-ray image, and a fourth-type cross region in the effective atomic number image based on the first-type cross region; determining a multimodal fusion image based on the second, third, and fourth-type cross regions; and identifying the liquid type of the liquid to be inspected based on the multimodal fusion image. The present invention can improve the accuracy of liquid type identification results.

The application discloses a material identification method based on adaptive quantitative decomposition, and establishes a polynomial relationship between coefficients participating in material identification and energy and effective atomic number in the interaction of rays and materials. Then, a plurality of known materials are used as calibration materials to perform scanning and reconstruction. Based on the linear attenuation coefficients of different energy regions of the calibration materials, the real effective atomic number and density of the calibration materials, and the polynomial relationship obtained previously, the effective energy of the corresponding energy region is determined. In actual operation, after scanning and reconstruction of the material to be decomposed, the effective energy is determined through calibration, the linear attenuation coefficients of different energy regions are only related to the effective atomic number and density, and through simultaneous solution of two ray and material interaction formulas containing variable parameters, the effective atomic number and density of the scanned material can be accurately obtained. The application can automatically adjust the related coefficients according to different materials, thereby improving the decomposition precision.

To provide image processing device, method, and program capable of analyzing tissue of interest by component.SOLUTION: An image processing device for processing an image acquired by an X-ray computer tomography apparatus capable of measuring an effective atomic number includes a processor. The processor displays at least one of a plurality of images acquired by the X-ray computer tomography apparatus in a display unit, receives settings of a first region on an image displayed in the display unit, receives settings of an effective atomic number, which is an object to be analyzed, extracts a pixel including a component of the effective atomic number in the first region, extracts a second region including a component of the effective atomic number in the first region, specifies the shape of the second region, and displays the shape of the second region in the display unit.SELECTED DRAWING: Figure 5

The invention relates to a urinary calculus component intelligent analysis method and system, and relates to the technical field of urinary calculus component analysis. The intelligent urinary calculus component analysis method is applied to calculus type identification and comprises the following steps: acquiring a urinary calculus atomic number image corresponding to a dual-energy abdomen image; extracting a plurality of component percentages of peak values corresponding to a plurality of bar diagrams corresponding to effective atomic numbers in the urinary calculus atomic number image; and based on a plurality of component percentages corresponding to the plurality of bar maps and a plurality of set stone type component percentage intervals, identifying a stone type corresponding to the dual-energy abdomen image. According to the embodiment of the invention, intelligent stone type identification can be realized.

In the case of a liquid material contained in a container without having a shape, it is very difficult to accurately predict the type or physical properties of the liquid, so that there is a problem that the accuracy or detection rate is very low.SOLUTION: The present invention relates to a method and system for detecting an object capable of improving a detection rate of dangerous materials such as liquid explosives as well as existing explosives, and may include (a) preparing an X-ray transmission image of an object, (b) calculating an effective atomic number value (Zeff) using the X-ray transmission image, and (c) classifying a target article image from the X-ray transmission image using the effective atomic number value and reconstruction of a multi-energy image for each energy band.SELECTED DRAWING: Figure 1

There are provided image processing apparatus, method, and program which can analyze a tissue of interest for each component. An image processing apparatus configured to process an image obtained by an X-ray computed tomography device capable of measuring an effective atomic number includes a processor. The processor displays at least one of a plurality of images obtained by the X-ray computed tomography device on a display unit, receives setting of a first region on the image displayed on the display unit, receives setting of an effective atomic number as an analysis target, extracts a pixel including a component of the effective atomic number in the first region and extracts a second region including the component of the effective atomic number in the first region, specifies a shape of the second region, and displays the shape of the second region on the display unit.