23 results about "Structured illumination microscopy" patented technology

The application provides a motion-resistant structured illumination microscopy method based on principal component analysis (mrPCA-SIM), which can effectively compensate for non-uniform pixel offset and phase error in original illumination images. Compared with the traditional method, the application can realize more stable imaging quality under complex and unstable conditions, and is expected to realize more compatible and flexible live cell super-resolution imaging.

The invention belongs to the field of biomedicine, and discloses a method and a kit for monitoring a lysosome acidification process mediated by mitochondrial-lysosome interaction. According to the method, an LYSO-PZ probe with a specific structure is used for marking cell lysosome contents, a pH rodo dye and a lysosome membrane marker sfGFP-LAMP1-mCherry are combined for monitoring the pH value and membrane positioning of the lysosome respectively, then a three-channel fluorescence image is obtained through a structural illumination microscope (SIM), and the fluorescence intensity ratio is quantitatively analyzed. In addition, the method further comprises a step of forming mitochondrial-lysosome contact (MLC) through optogenetics regulation, related protein binding is induced through blue light, fluorescence intensity changes before and after MLC formation are compared, and MLC-mediated proton transport is verified. A complete monitoring system is established for the first time, lysosome acidification can be accurately monitored, information can be obtained in multiple dimensions, and the method has important clinical application value and wide market prospects.

The application belongs to the field of biomedicine, and discloses a method and a kit for monitoring a process of mitochondrion-lysosome interaction-mediated lysosome acidification. The method is characterized in that a cell lysosome content is first labeled with a LYSO-PZ probe with a specific structure, a pHrodo dye and a lysosome membrane marker sfGFP-LAMP1-mCherry are combined to monitor the pH value and membrane localization of the lysosome, respectively, then three-channel fluorescence images are acquired through a structured illumination microscope (SIM), and the fluorescence intensity ratio is quantitatively analyzed. In addition, the method further comprises a step of optogenetic regulation of mitochondrion-lysosome contact (MLC) formation, the fluorescence intensity change before and after the formation of MLC is compared through blue light induction of related protein binding, and the proton transport mediated by MLC is verified. The application first establishes a complete monitoring system, can accurately monitor lysosome acidification, and has important clinical application value and broad market prospect.

The invention discloses an atomic force microscope morphology measurement error correction method and device, and belongs to the technical field of image processing. Comprising the steps that a first scanning image and a second scanning image are obtained, the first scanning image is obtained by scanning a sample through structured illumination obvious micro-imaging SIM, and the second scanning image is obtained by scanning the sample through an atomic force microscope AFM; according to the first scanning image, morphology measurement error detection is carried out on the second scanning image to obtain an error position, and the error position is a position where morphology measurement errors exist in the second scanning image; and correcting the morphology measurement error of the error position according to the first scanning image to obtain a target morphology image. Therefore, the morphology measurement error caused by the acting force between the probe and the sample can be guided and corrected through the SIM optical data, so that the accurate sample morphology can be obtained, and the accuracy and reliability of sample morphology measurement are improved.

The invention relates to a structured illumination obvious micro-imaging method based on an adaptive Hilbert norm, and aims to solve the problems that an illumination parameter estimated value obtained by an existing SIM reconstruction algorithm is inaccurate and reconstruction artifacts occur under the condition that illumination stripes are not uniform. The method comprises the following steps: decomposing a collected single-frame or multi-frame SIM original image into a structure part, a texture part and a noise part; an energy minimization model containing a total variation norm and an adaptive Hilbert norm is constructed, and a part representing the illumination pattern texture is accurately extracted; and carrying out iterative reconstruction on the extracted illumination pattern image and the SIM original image to finally obtain a super-resolution image. Compared with a traditional method, the method has the advantages that the illumination pattern can be accurately extracted from the single-frame original image, non-uniform illumination stripes with local bending are effectively processed, and a more accurate super-resolution reconstruction result is obtained. The method is suitable for various reconstruction methods and application scenes, and has a good application prospect in improvement of SIM imaging quality and imaging flux.

The application discloses self-supervised structured light illumination super-resolution microscopic image denoising, comprising: providing a denoising network with a super-resolution reconstruction module and a super-resolution denoising module, the super-resolution reconstruction module is configured to perform super-resolution reconstruction on an original image to output a super-resolution reconstructed image, the super-resolution denoising module is configured to perform denoising processing on the super-resolution reconstructed image to output a super-resolution denoised image, the super-resolution denoising module is built by using a neural network, and the denoising network is trained in the following manner before deployment: providing at least one set of original images; the original images are split into training input original images and training target original images in the manner of first downsampling and then upsampling; the training input original images and the training target original images are augmented to generate a set of training input original images and a set of training target original images; and a training network model of a self-supervised deep learning network is established for the super-resolution image denoising network.

The invention provides a microscopic imaging method, device, equipment and system and a storage medium, and relates to the technical field of microscopic imaging, and the method comprises the steps: obtaining the current state and brightness variation of a fluorescence labeled sample; determining an illumination intensity adjustment amount based on the current state and the brightness variation; when the illumination intensity of the structural illumination microscope is adjusted to target illumination intensity, a first microscopic image of the fluorescence labeling sample collected by the structural illumination microscope is obtained, and the target illumination intensity is the illumination intensity obtained based on the illumination intensity adjusting amount; and obtaining a target microscopic image of the fluorescence labeled sample based on the first microscopic image. According to the method, the influence of phototoxicity on the sample can be reduced, so that the imaging quality is improved.

This application provides a method, apparatus, device, system, and storage medium for microscopic imaging, relating to the field of microscopic imaging technology. The method includes: acquiring the current state and brightness change of a fluorescently labeled sample; determining a light intensity adjustment amount based on the current state and brightness change; acquiring a first microscopic image of the fluorescently labeled sample using a structured illumination microscope when the illumination intensity is adjusted to a target illumination intensity, wherein the target illumination intensity is the illumination intensity obtained based on the light intensity adjustment amount; and obtaining a target microscopic image of the fluorescently labeled sample based on the first microscopic image. This method can reduce the phototoxicity to the sample, thereby improving imaging quality.

The technology disclosed relates to structured illumination microscopy (SIM). In particular, the technology disclosed relates to capturing and processing a large number of image tiles on a large image plane in real time, dividing them into sub-tiles, efficiently processing the sub-tiles, and generating an enhanced resolution image from the sub-tiles. The enhanced resolution image can be combined into an enhanced image and can be used for subsequent analysis steps.

The present disclosure relates to imaging systems and methods of use thereof for imaging with simplified structured illumination microscopy (SIM). The present methods may be simpler and less costly to build and maintain that existing SIM systems. The imaging methods may include oscillating a portion of the imaging system to scan an illumination pattern across a field of view of the sample.

The invention belongs to the field of three-dimensional topography measurement, and particularly discloses a structural illumination microscope surface topography reconstruction method and system based on virtual double differential motion, and the method comprises the steps: carrying out the SIM reconstruction and modulation and demodulation of a scanned and collected structural light image, and obtaining an axial modulation response curve of a full-view-field pixel; respectively and virtually moving the scanning position forwards and backwards for the same axial offset distance along the scanning direction to obtain corresponding virtual front and back focus modulation response curves AMR1 and AMR2; based on the sum of Gaussian functions approximated by AMR1 and AMR2, a virtual double-difference modulation response curve is constructed, and z represents a scanning position; when the virtual double-differential modulation response curve crosses a zero point, the corresponding scanning position is the surface height of the sample, and corresponds to the peak position of AMR; therefore, the surface morphology reconstruction of the sample is realized. According to the invention, rapid and high-precision morphology reconstruction of a complex surface can be realized.

A digital imaging method is disclosed that can be used for structured illumination microscopy to obtain a super-resolution image of a sample having a distribution of fluorophores that emit light when illuminated by an excitation beam, the digital imaging method using an innovative algorithm, wherein a super-resolution image is reconstructed in a cut plane of the sample on which the excitation beam is focused, while also taking into account light contributions from fluorophores located in the out-of-focus plane. The digital image processing method of the present disclosure may be implemented by a computer-run program, and may be used in a related structured illumination microscopy method (SIM).

A spatial filter for a confocal microscope comprising a spinnable disk locatable in an optical path of the confocal microscope between a coherent light source providing excitation light and a target. The spinnable disk comprises a first region providing a first optical path through the disk, the first region comprising a first optical path length for the excitation light transmitted through the disk and a second region providing a second optical path through the disk, the second region comprising a second optical path length for the excitation light transmitted through the disk, the second optical path length different from the first optical path length and thereby imparting a second phase shift to the excitation light transmitted through the second region that is different from a first phase shift imparted to the excitation light transmitted through the first region.

In the described embodiment, a method for image reconstruction is implemented, comprising acquiring a set of original images corresponding to a plurality of phases of an illumination pattern. The image reconstruction method further includes separating the original spectrum of each original image into a baseband spectrum and at least two modulation shift spectrums using an inverse matrix, and demodulating the set of original images to generate a demodulated image. A high pass filter is applied to the baseband spectrum and a low pass filter is applied to the spectrum of the demodulated image in order to generate a corrected baseband spectrum. The corrected baseband spectrum is combined with the at least two modulation shifted spectrums to generate a synthesized spectrum. An inverse Fourier transform is performed on the synthetic spectrum to produce a reconstructed image.

Microscopy methods and devices that use structured illumination are described. An example method includes providing multiple digital raw images of a sample that are recorded sequentially a microscope and obtained by illuminating the sample in different phases with periodically structured illumination light. The method includes, determining, using a structured illumination microscopy (SIM) reconstruction method, an intermediate imaging result for the sample with an increased resolution compared to the raw images, where the resolution is higher than the diffraction-limited resolving power of the microscope. In addition, the above method reduces or suppressed image artifacts.

The present disclosure relates to imaging systems and methods of use thereof for imaging with simplified structured illumination microscopy (SIM). The present methods may be simpler and less costly to build and maintain that existing SIM systems. The imaging methods may include oscillating a portion of the imaging system to scan an illumination pattern across a field of view of the sample.

Various embodiments for a three-dimensional structured illumination microscopy system having a mirror positioned in diametric opposition to the objective for producing additional illumination components by a fourth beam generated by the mirror and a computational means for accomplishing the same are disclosed herein.

The application discloses a kind of structure light illumination super-resolution microscopic imaging methods based on four-beam interference.The method uses four-beam coherent interference illumination design, and combines the composite frequency domain filtering strategy based on three-dimensional OTF physical constraint, under the premise that no need to carry out any hardware modification to the light path of traditional interference structure light microscope (SIM) system, first realize the lateral two times super-resolution improvement and excellent optical sectioning ability, effectively overcome the off-focus background interference problem faced in thick sample imaging in the prior art.In addition, the application introduces an illumination parameter estimation algorithm based on principal component analysis (PCA), while significantly reducing the computational complexity, further improves the accuracy and stability of parameter estimation.Experimental results show that the method can high-resolution, high-fidelity, high-robustness and high-efficiency imaging for thick living cell samples, break through the limitation that traditional two-dimensional super-resolution SIM is mainly suitable for thin living cell imaging, has wide application potential and practical value.

This invention discloses a multispectral super-resolution imaging device based on compressed sensing, belonging to the field of optical microscopy. The device comprises a light source and beam expansion system, a polarization modulation and structured illumination microscopy system, an coded spectral compression imaging system, a synchronization control system, and a data processing and reconstruction system. This invention solves the problem of the trade-off between increasing the number of spectral channels and maintaining imaging speed in existing spectral-resolution structured light super-resolution microscopy. By combining compressed sensing with single-snapshot spectral coding and dispersive imaging, structured illumination, and a two-step depth unfolding network reconstruction algorithm based on a physical model, this invention can rapidly and synchronously reconstruct super-resolution images of multiple spectral channels with only a small number of compressed images acquired, significantly improving the spectral resolution of imaging without sacrificing the imaging frame rate.

The present disclosure relates to imaging systems and methods of use thereof for imaging with simplified structured illumination microscopy (SIM). The present methods may be simpler and less costly to build and maintain that existing SIM systems. The imaging methods may include oscillating a portion of the imaging system to scan an illumination pattern across a field of view of the sample.

A structured illumination microscopy (SIM) system comprises: a light source; a light-structuring component to provide light from the light source with a SIM pattern for performing illuminations of a sample at a substrate having a substrate pattern, wherein a pitch of the SIM pattern is based on a characteristic of the substrate pattern; and an image sensor to detect emissions that the sample generates in response to the illuminations.

The present application relates to a kind of structure light illumination microscopic imaging method based on adaptive hilbert norm, the present application aims at solving the problem of inaccurate illumination parameter estimation value and reconstruction artifact under the condition of uneven illumination stripe in existing SIM reconstruction algorithm.The method of the present application decomposes the single frame or multiple frame SIM original image collected into structure, texture and noise part;By constructing an energy minimization model containing total variation norm and adaptive hilbert norm, the texture part representing illumination pattern is accurately extracted;The extracted illumination pattern image is iteratively reconstructed with SIM original image, and finally the super-resolution image is obtained.Compared with the traditional method, the present application can accurately extract the illumination pattern from single frame original image, effectively process the non-uniform illumination stripe with local bending, and obtain more accurate super-resolution reconstruction result.The method is suitable for a variety of reconstruction methods and application scenarios, and has good application prospect in the improvement of SIM imaging quality and imaging flux.

The invention discloses a super-resolution structure illumination obvious micro-imaging method and system and computer equipment, belongs to the field of computational imaging, and solves the problems that traditional SIM reconstruction depends on global parameters and is sensitive to low SNR, and an existing deep learning method has over-smoothness and global discrimination neglects spatial heterogeneity. Comprising the following steps: acquiring a single-frame structured light illumination input image embedded with multi-direction illumination information; performing Fourier interpolation up-sampling on the input image to match the super-resolution reconstruction scale; constructing a super-resolution reconstruction network based on the conditional generative adversarial network, and designing a multi-scale Markov discriminator to match super-resolution reconstruction tasks of organelles of different scales; training the super-resolution reconstruction network based on the double-domain loss, and obtaining a super-resolution structured illumination obvious micro-imaging model; and carrying out super-resolution structured illumination obvious micro-imaging by adopting the super-resolution structured illumination obvious micro-imaging model. The method is suitable for living cell super-resolution imaging scenes.