41 results about "Phase-contrast imaging" patented technology

The invention relates to the technical field of rubber performance evaluation, in particular to a performance data analysis and evaluation method for a rubber material. The method comprises the following steps: acquiring X-ray scanning data of a rubber sample; performing phase contrast imaging on the X-ray scanning data of the rubber sample to obtain projection data of the rubber sample; performing back projection reconstruction on the projection data of the rubber sample to obtain three-dimensional structural data of the rubber material; carrying out multi-parameter environmental simulation loading on the rubber sample to obtain environmental response data of the rubber material; dynamically collecting the environmental response data of the rubber material to obtain deformation process data of the rubber material; synchronously recording and analyzing the deformation process data of the rubber material to obtain a stress-strain characteristic pattern of the rubber material; and performing polarization spectrum excitation on the rubber sample based on the rubber material stress-strain characteristic pattern to obtain rubber molecular chain fluorescence data. According to the invention, the reliability and accuracy of rubber material performance evaluation are improved.

The invention belongs to the technical field of optical imaging, and discloses a multifunctional image edge enhancement device based on spiral phase contrast imaging, which comprises a light source system, an optical imaging system and an edge enhancement detection system which are arranged in sequence, the light source system is used for generating collimated linear polarization laser; the optical imaging system comprises a first 4-f system and a round hole diaphragm which are sequentially arranged on a light path; a sample to be tested is arranged between the light source system and the first 4-f system; the edge enhancement detection system comprises a first lens, a vortex wave plate, a second lens and an imaging unit which are sequentially arranged on a light path; the first lens and the second lens form a second 4-f system; linearly polarized laser output by the light source system is transmitted by a to-be-detected sample, enters the first lens after passing through the first 4-f system and the round hole diaphragm, and then is imaged on the imaging unit after passing through the vortex wave plate and the second lens in sequence. According to the invention, edge enhancement can be realized, and the contrast and resolution of the image are improved.

To provide an X-ray phase imaging apparatus and an image processing method for improving contrast and visibility of an image photographed by a phase contrast method.SOLUTION: According to an aspect of the present invention, there is provided an X-ray phase imaging apparatus comprising an X-ray source, a detector configured to detect X-rays emitted from the X-ray source to a subject, and an image processing unit configured to generate an image of the subject, the image processing unit includes a storage unit in which a plurality of noise correction images for correcting a luminance variation between pixels are stored separately for brightness and darkness, and an image generation unit that generates a luminance image of the subject by irradiating the subject with X-rays, generates a plurality of corrected images of the subject by correcting the luminance image according to the noise correction image, and generates one subject image by selecting the plurality of corrected images according to a threshold value.SELECTED DRAWING: Figure 5

The invention provides an X-ray single projection imaging wood type intelligent identification method and system and a medium, and the method comprises the steps: carrying out the multi-time translation through an X-ray phase contrast imaging system, and obtaining single projection images of different positions of a wood sample, and taking the single projection images as an image data set; preprocessing the single projection image to obtain a preprocessed image data set; training a deep learning model by using the preprocessed image data set; the deep learning model is an improved OfficientNetV2 model, and the depth learning model is an improved EfficientNetV2 model; and obtaining a to-be-tested sample, shooting a single projection image, preprocessing the single projection image, and inputting the preprocessed image into the trained deep learning model for sample classification. According to the invention, based on phase contrast X-ray single projection imaging, through improving a deep learning network model, high-accuracy and high-efficiency intelligent identification of a wood sample is realized.

A quantitative phase contrast imaging system comprises a light source configured to generate light and to direct the light to a sample, wherein the light comprises nonlinearly polarized light; a first lens configured to receive light from the sample; a phase filter, wherein the first lens is configured to focus the light from the sample onto the phase filter, and the phase filter is configured to modulate multiple components of the nonlinearly polarized light simultaneously (e.g., geometric phase interferometry); a second lens configured to receive light from the phase filter; and a polarized camera, wherein the second lens is configured to collimate the light beam from the phase filter to the polarized camera and the polarized camera is configured to image the sample in response to the light from the phase filter. In absence of the second lens, the camera can be placed at the image plane.

The present disclosure provides example embodiments for automatically or semi-automatically classifying cells in microscopic images of biological samples. These embodiments include methods of selecting training sets for the development of a classifier model. The disclosed selection embodiments can allow for retraining of a classifier model using training examples that have undergone the same or similar culture conditions as a target sample. These selection embodiments can reduce the human effort required to specify the training examples. The disclosed embodiments also include classifying individual cells based on metrics determined for the cells using phase contrast imaging and out-of-focus brightfield imaging. These metrics can include size, shape, texture, and intensity-based metrics. These metrics are determined based on segmentation of the underlying imagery. In some embodiments, the segmentation is based on phase contrast imaging and / or out-of-focus brightfield imaging of the biological sample.

A system for analyzing biological components in a biological sample, wherein the system comprises a planar surface, and wherein the system is configured to perform a procedure comprising: (a) arranging a spatially connected biological sample adjacent to the planar surface, wherein: the spatially connected biological sample comprises a tissue sample, the tissue sample comprises a plurality of cells, the planar surface comprises glass, plastic, or a combination thereof, the planar surface further comprises a plurality of binding sites, the plurality of binding sites is arranged in a two-dimensional pattern on the planar surface, the planar surface comprises at least 10⁵ binding sites, each of the plurality of binding sites comprises a plurality of single-stranded oligonucleotides, and the plurality of single-stranded oligonucleotides is coupled to the planar surface.at least one subset of the plurality of single-stranded oligonucleotides comprises: (i) a binding sequence comprising a plurality of thymine bases configured to bind to poly-A sequences, (ii) a unique molecular identifier, (iii) a barcode associated with a position on the planar surface, and (iv) a sequencing primer, and each oligonucleotide of the subset of the plurality of single-stranded oligonucleotides comprises at least 50 nucleotides; (b) imaging at least a portion of the spatially linked biological sample, wherein the imaging comprises bright-field imaging, phase-contrast imaging, fluorescence imaging, or a combination thereof; (c) releasing nucleic acids from the spatially linked biological sample; and (d) capturing at least one subset of the nucleic acids on at least the subset of single-stranded oligonucleotides, thereby recovering the captured nucleic acids.the captured nucleic acids are immobilized on the flat surface.

This invention belongs to the field of micro / nano fabrication and optical testing technology, specifically relating to a high-resolution test card for dielectric materials in the EUV and soft X-ray bands. The test card includes a substrate and a Siemens star test pattern formed thereon. The test card uses silsesquioxane (HSQ) as the structural material and is fabricated using electron beam lithography. The structural height can reach 500 nm with a minimum linewidth of 10 nm. This invention utilizes the dual absorption and strong phase modulation capabilities of HSQ in the EUV / soft X-ray bands, making it suitable for both absorption contrast and phase contrast imaging modes in system resolution calibration and performance evaluation. This test card offers advantages such as standardized patterns, high resolution, adjustable contrast, and good fabrication consistency, providing crucial metrological support for the performance testing of high-end EUV / soft X-ray optical imaging and lithography systems.

The present invention relates to an X-ray multi-contrast image fusion characterization method based on unsupervised feature learning, and belongs to the field of deep learning and X-ray multi-contrast imaging technology. The method comprises: obtaining absorption, phase, and dark field contrast computed tomography images of X-ray grating imaging; constructing a generative adversarial network model based on unsupervised feature learning; training a generative adversarial network model based on unsupervised feature learning; using the trained model to fuse the absorption, phase, and dark field contrast computed tomography images to obtain a fused image, and using the fused image to characterize the inspected object. Compared with the existing X-ray grating multi-contrast imaging technology, the embodiment of the present invention can better utilize the advantage of X-ray grating differential phase contrast imaging that can produce three different contrast images at the same time, and perform fusion characterization on the three contrast images.

Proposed is a microscope enabling differential phase contrast imaging of oblique focal plane and a method for operating the same, which can image a large area 3D surface by scanning and photographing in a horizontal direction a focal plane tilted by applying an oblique plane microscopy (OPM) technology that tilts a focal plane of a photographing area of a microscope. The microscope includes a sample photographing module for photographing a sample and an imaging generator for generating a sample imaging on the basis of an image of the sample photographed in the sample photographing module, wherein the sample photographing module includes a light source unit for radiating light to the sample, an objective lens for obtaining transmitted light from the sample, and an imaging information acquisition unit for obtaining imaging information of the sample through the transmitted light.

This invention provides a method for charged particle beam (CPB) phase contrast imaging. [Solution] In a CPB system, the phase contrast image is obtained by directing a sample-modulated CPB to the phase plate so that it has a diffraction plane displaced from the phase plate. Based on the interference fringes of the image, the lateral displacement of the CPB relative to the phase plate can be estimated and adjusted.

According to the method, a programmable LED lamp is installed on a microscope condenser, a light source is adjusted to the height of a sample table, then four inclined illumination modes including the upper, the lower, the left and the right are switched, part of coherent light is obliquely incident to a sample, at the moment, emergent light waves carry amplitude and phase information of the sample, and the sample can be observed in a high-resolution non-destructive mode. The sample is collected by the high magnification objective lens, the corresponding intensity image is collected by the CCD camera, and the collected original image is subjected to deconvolution by using the differential phase contrast imaging principle to obtain the biological information such as the thickness and the dry mass of the sample. A programmable annular LED is adopted as an illumination light source to enhance the phase contrast of a low-frequency space and reduce noise interference, and the illumination light source forms an angle of 15 degrees with a sample platform and directly irradiates a sample to generate a uniform illumination light source. The submicron organelle can be dynamically observed in real time through the high numerical aperture objective lens, and organelle edge extraction and 3D form reconstruction are obtained by using a deconvolution reconstruction algorithm.

The present application belongs to the field of micro-nano processing and X-ray optical testing technology, and particularly relates to a high-resolution test card in hard X-ray band and a preparation method thereof. The test card adopts electron beam lithography combined with proximity effect correction technology to prepare an HSQ template pattern, forms a Siemens star structure with a minimum line width of 10 nm and a height of 500 nm, and then covers a metal working layer on the template surface through atomic layer deposition technology. The HSQ template pattern has a duty cycle less than 1, effectively improving the aspect ratio of the pattern. The covering of the metal working layer doubles the line density of the final pattern. The present application breaks through the resolution limit of the traditional test card, solves the problem of preparation of high-aspect-ratio nano structures, and has simple and reliable process, and is suitable for resolution calibration of absorption contrast and phase contrast imaging systems in hard X-ray band, thereby providing key technical support for performance evaluation of high-end X-ray optical systems.

The invention relates to an X-ray multi-contrast image fusion representation method based on unsupervised feature learning, and belongs to the technical field of deep learning and X-ray multi-contrast imaging. The method comprises the following steps: acquiring absorption, phase and dark field contrast computed tomography images of X-ray grating imaging; constructing a generative adversarial network model based on unsupervised feature learning; training a generative adversarial network model based on unsupervised feature learning; and fusing the absorption, phase and dark field contrast computed tomography images by using the trained model to obtain a fused image, and representing a detected object by using the fused image. Compared with an existing X-ray grating multi-contrast imaging technology, the X-ray grating differential phase contrast imaging method and device can well utilize the advantage that X-ray grating differential phase contrast imaging can generate three different contrast images at the same time, and fusion characterization is conducted on the three contrast images.

The invention relates to the technical field of microscopic detection, in particular to a microscopic imaging system with bright field imaging and phase difference imaging, which comprises an imaging module, a bright field imaging illumination module, a focusing module, a phase difference imaging illumination light source module and a control module. The problems that in the prior art, the switching time is long, the definition degree of images is prone to being affected in the switching process, the target form of bright field image and phase difference image shooting is changed, and result contrastive analysis is not facilitated are solved.

The present invention discloses a method for grayscale stereo conversion of images based on GSCGAN, comprising the following steps: Step 1: constructing a bright field mode image set, a phase contrast mode image set, and a differential interference mode image set; Step 2: using the light propagation convolution formula in phase contrast imaging and differential interference imaging to replace the convolution propagation operation in the traditional GAN ​​to construct a complex-valued GAN and establish a preliminary GSCGAN model; Step 3: inputting the training image into the preliminary GSCGAN model for training to obtain the GSCGAN model; Step 4: inputting the transparent target sample image into the GSCGAN model for testing to obtain the result image. The present invention uses a model based on GSCGAN to perform grayscale stereo conversion on the transparent sample image, and obtains an image with a phase contrast interference effect or a differential interference effect. The constructed pattern discriminator D m It can determine whether an image is a phase contrast image or a differential interference effect image, allowing the input of one image to output two different effect images. It also proposes a grayscale loss function to effectively preserve the correct information while avoiding the effect of color confusion on the result.

The present invention discloses an oblique phase contrast imaging device for an inverted biological microscope, belonging to the field of optical microscopic imaging technology. The device comprises an oblique phase contrast imaging plate disposed below the condenser of the inverted biological microscope, and an oblique phase contrast light source disposed on a frame support surface below the stage of the inverted biological microscope. The light beam emitted by the oblique phase contrast light source is emitted onto the oblique phase contrast imaging plate via a wave plate on the stage of the inverted biological microscope. The present invention solves the problem of poor performance and complex operation when observing brightfield fluorescence using an inverted biological microscope.

The present invention relates to the technical field of rubber performance evaluation, and in particular to a method for analyzing and evaluating performance data of rubber materials. The method comprises the following steps: acquiring X-ray scanning data of a rubber sample; performing phase contrast imaging on the X-ray scanning data of the rubber sample to obtain projection data of the rubber sample; performing back-projection reconstruction on the projection data of the rubber sample to obtain three-dimensional structural data of the rubber material; subjecting the rubber sample to multi-parameter environmental simulation loading to obtain environmental response data of the rubber material; dynamically collecting the environmental response data of the rubber material to obtain deformation process data of the rubber material; synchronously recording and analyzing the deformation process data of the rubber material to obtain a stress-strain characteristic diagram of the rubber material; and performing polarization spectral excitation on the rubber sample based on the stress-strain characteristic diagram of the rubber material to obtain fluorescence data of the rubber molecular chain. This invention improves the reliability and accuracy of rubber material performance evaluation.

The invention relates to an automobile power battery shell micropore nondestructive testing method based on synchrotron radiation X-ray phase imaging, and relates to the technical field of photoelectric detection / image recognition / nondestructive testing. The method comprises the following steps: constructing a uniform irradiation field and acquiring data; phase inversion and electron cloud density reconstruction; feature fusion and abnormal region identification; performing defect classification and risk assessment; and performing parameter feedback and system optimization. According to the automobile power battery shell micro-pore nondestructive testing method based on synchrotron radiation X-ray phase imaging, phase change caused by electron cloud density disturbance is imaged by utilizing high coherence of synchrotron radiation X-rays and a phase contrast imaging principle; the sensitivity to the internal microstructure of the low-atomic-number material is several orders of magnitude higher than that of absorption imaging, micropores which cannot be seen by a traditional method can be clearly recognized, and the detection sensitivity is improved.

A mask for use in a speckle-based x-ray or neutron phase contrast imaging system and methods of making the mask are disclosed. The mask may either absorb or change the phase of the incident x-ray or neutron beam. The mask in various embodiments has consistent statistics across the mask, is locally unique (thereby avoiding ambiguous correlations), has a speckle size on the order of the imaging system's resolution, has a speckle pattern that is visible through the sample being imaged, and / or is matched to the energy level of the imaging system and the sample density. These mask attributes are controlled by the method and materials used in the fabrication of the mask. Various embodiments use a pseudo-random binary array for generating the required speckle pattern.

The invention discloses an image phase recovery method and device based on X-ray coaxial phase contrast imaging, and the method comprises the steps: carrying out the first processing of an initial intensity projection image through a convolution block, and obtaining feature data X1; performing iteration processing on the image data X1 for four times through maximum pooling operation and a convolution block to sequentially obtain feature data X2, X3, X4 and X5; processing the feature data through an up-sampling convolution block and a convolution block in sequence according to a set sequence to obtain a phase-shifted image after phase recovery, and performing Fresnel propagation processing on the phase-shifted image to obtain a calculated intensity projection image; performing calculation through a loss function calculation strategy to obtain an L1 loss function value; and iteratively optimizing and updating parameters of the recovery network through an L1 loss function value and a back propagation algorithm, and when the loss function value converges, outputting a final phase shift image and obtaining a reconstructed image through filtering back projection reconstruction. According to the invention, a reconstructed image which clearly shows internal material information can be obtained.

The invention is applicable to the field of in-vitro diagnostic equipment, and discloses a sample analyzer, an imaging device and a lighting device. The sample analyzer comprises a sample bearing device, a lighting device, an imaging device and a controller, the lighting device comprises a light source, a first polarization piece and a second polarization piece, a first polarization part is formed on the first polarization piece, a second polarization part and a light transmitting part are formed on the second polarization piece, and the first polarization part is used for generating polarization on light irradiated on the first polarization part in the first polarization direction; the second polarization part is used for polarizing the light irradiated on the second polarization part along a second polarization direction, and the first polarization direction is approximately perpendicular to the second polarization direction; when light rays emitted by the light source sequentially pass through the first polarization part and the light transmitting part and are emitted to a to-be-detected sample, phase contrast illumination light rays are formed; when light emitted by the light source is emitted to the to-be-detected sample through the second polarization part and the light-transmitting part, bright-field illumination light is formed. The structure for switching phase contrast imaging and bright field imaging is simple, and the cost is low.

The invention provides an X-ray single projection imaging seed intelligent classification method and system and a medium, and the method comprises the steps: obtaining projection images of different seed samples at different angles through an X-ray phase contrast imaging system, and taking the projection images as an image data set; pre-processing the projection image to obtain a pre-processed image data set; training a deep learning model by using the preprocessed image data set; the deep learning model adopts an Inception-ResNet-V2 network architecture, and the depth learning model adopts a depth learning model; and obtaining a sample to be tested, shooting a single projection image at any angle, preprocessing the single projection image, and inputting the preprocessed image into the trained deep learning model for classifying the seed sample. According to the method, through collaborative innovation of non-destructive and efficient phase contrast X-ray single projection imaging and deep learning, the internal texture of the seeds is obtained, and accurate classification of the seeds can be losslessly and efficiently achieved only through a single X-ray projection image.

Real-space optical signal processing is provided by optical angular filters that act on amplitude and / or phase of zero order light passing through a resonant diffractive optical device. One application is to phase contrast microscopy, where the diffractive optical device can be configured to have an amplitude and phase response suitable for phase contrast microscopy. For example, 60% or more intensity attenuation of the zero order light, combined with a phase shift of the zero order light by + / −90 degrees.

The invention discloses a visualization system for a single microcavitation in an ultrasonic field based on X-ray phase contrast imaging. The device comprises an ultrasonic experiment box which is used for accommodating a liquid medium and generating microcavitation; the X-ray source is used for generating high-brightness and collimated X-rays, and the X-rays can penetrate through the ultrasonic experiment box; the image acquisition system comprises a scintillation crystal, a microscope and a high-speed camera, the scintillation crystal is used for converting X-rays into visible light, the microscope is used for amplifying the visible light, and the high-speed camera is used for capturing an amplified visible light image; the ultrasonic generator is connected to the phased array ultrasonic transducer array element and is used for generating a focused ultrasonic beam and dynamically adjusting the focus position of the focused ultrasonic beam; according to the method, focused ultrasound is utilized, a large number of micro-cavitation bubbles can be generated at the ultrasonic focus, the ultrasonic intensity is reduced at a certain distance on the periphery of the focus, the acoustic cavitation effect is weak, so that the micro-cavitation bubbles are dispersed, and visualization of a single micro-cavitation bubble can be achieved.

The invention discloses an oblique phase difference imaging device for an inverted biological microscope, which belongs to the technical field of optical microscopic imaging and comprises an oblique phase difference imaging plate arranged below a collecting lens of the inverted biological microscope and an oblique phase difference light source arranged on a rack bearing surface below an objective table of the inverted biological microscope. And a light beam emitted by the oblique phase difference light source is emitted to the oblique phase difference imaging plate through a wave plate on an objective table of the inverted biological microscope. The problems that the effect is poor and the operation is complex when the inverted biological microscope is used for observing fluorescent light in a bright field are solved.

The phase contrast imaging simulation method comprises the steps that a light source, an imaged object, an object plane and an image plane are sequentially arranged in a simulation environment in the photon emission direction, and the object plane is divided into a plurality of object plane sub-areas; the interaction between the photons and the imaged object in the process of penetrating through the imaged object is simulated; for each object plane sub-region in the plurality of object plane sub-regions, determining the energy and phase distribution of a wave surface corresponding to the object plane sub-region based on the energy and phase of all photons penetrating through the imaged object to reach the object plane sub-region; based on the energy and phase distribution of each wave surface corresponding to each object plane sub-region, determining the energy distribution of all wave surfaces reaching the image plane; and generating a simulated image of the imaged object based on the energy distribution from the wave surfaces corresponding to the plurality of object plane sub-regions to the image plane. According to the invention, while phase contrast imaging is accurately simulated, time and computing resources required by simulation operation can be reduced.

This invention discloses an aberration correction and quantitative phase imaging method based on a physically driven neural field. The method constructs a physical forward model for differential phase-contrast imaging under partially coherent illumination conditions and implicitly represents the sample's complex transmission function and optical aberrations using a neural field. By jointly optimizing sample information and optical aberrations through a differentiable operator, it achieves an inversion solution from intensity information to the sample's phase distribution. This method overcomes the limitations of weak object approximation, achieving self-calibration of optical aberrations and high-precision phase recovery without additional calibration data or acquisition overhead. It is suitable for quantitative phase imaging of biological samples or micro / nanostructured samples.