1298 results about "Optical coherence tomography" patented technology

Systems and methods for detecting features, outputting feature representations, determining measurements, and combinations thereof using machine-learned algorithms are provided. In some embodiments, first sample data from a first characterization modality and second sample data from a second characterization modality are provided to a machine-learned algorithm. Improved feature detection, feature representation, and measurement may be realized by using multimodal data with a machine-learned algorithm. In some embodiments, a first characterization modality is an interferometric modality and a second characterization modality is a spectroscopic modality. A first characterization modality may be optical coherence tomography and a second characterization modality may be a diffuse spectroscopy modality, such as near-infrared spectroscopy. Sample data may be intraluminal and / or vascular data useful in characterizing a vascular system of a subject, such as a human.

The invention discloses a bone joint lesion area automatic labeling method and system based on image processing, and belongs to the field of bone joint lesion area labeling. According to the invention, a bone joint reflection signal is obtained by combining the polarization-state-adjustable laser light source with polarization-sensitive optical coherence tomography, and a three-dimensional birefringence distribution diagram is generated through matrix analysis. And after non-local mean filtering is carried out on the distribution map, a lesion edge contour is extracted based on a dynamic gradient amplitude, and a binary mask is generated. Mask pixels are converted into network nodes containing space coordinates, gradient directions and birefringence, and a topological network is constructed based on the Euclidean distance of adjacent pixels. The weight is calculated through the node intersection density and the birefringence, and a graph attention network is utilized to aggregate multi-layer features to extract lesion topological features. The features are mapped to a three-dimensional space to construct a lesion probability distribution field, an interactive labeling result is generated through contour surface extraction and transparency mixed rendering, and the accuracy of labeling the complex lesion area of the bone joint can be improved.

The invention belongs to the technical field of film quality analysis and evaluation, and particularly relates to a flexible circuit board film pressing quality detection and analysis method and system. The method comprises the steps of generating a self-adaptive scanning path based on a design file and surface deformation data; performing multi-modal data acquisition and fusion along a path through optical surface scanning, ultrasonic tomography and an optical coherence tomography imaging assembly; potential defects are positioned, and size, shape, position and defect type probability values are quantized; judging the authenticity of the defect by adopting a three-stage mechanism of cross-modal probability comparison, physical characteristic logic verification and multi-frame time sequence verification; and performing weighted scoring on the real defect matching acceptance standard table, and performing disqualification marking or outputting a process optimization suggestion to the pressing equipment according to a scoring result. According to the invention, the imaging limitation of the transparent coating layer is broken through, the internal interface layering and the precise detection of the microbubbles are realized, and the closed-loop control from detection to production adjustment is formed.

The present technology relates to systems and methods for objectively assessing accommodation of adjustable intraocular lenses ("AIOLs"). In some embodiments, a method of objectively assessing accommodation of an AIOL implanted within an eye of a patient includes receiving, via an accommodation assessment system, (a) first optical coherence tomography (OCT) geometric data associated with the AIOL when the eye is in a first accommodative state, and (b) second OCT geometric data associated with the AIOL when the eye is in a second accommodative state. The method next includes determining, based in part on a comparison of the OCT data, a first change to a thickness of an adjustable lens of the AIOL and / or a second change to a curvature of an optical surface of the AIOL. The method then includes determining, based in part on the first change and / or second change, a third change to an optical power of the AIOL.

The invention relates to the technical field of ophthalmologic image processing, and discloses a fundus blood vessel segmentation method based on multi-modal data. The method comprises the following steps: firstly, synchronously acquiring an optical coherence tomography image, a color fundus photographic image and a fluorescent angiography image to form multi-modal fundus data; preprocessing the eye fundus image data set to generate a standardized multi-mode eye fundus image data set; fusing heterogeneous features based on the data set, and constructing a multi-dimensional fundus feature space; using the space to train a deep learning segmentation network model, and generating an initial fundus blood vessel segmentation mask; carrying out confidence evaluation analysis on the initial mask to obtain a blood vessel segmentation result confidence distribution map; dividing blood vessel segmentation quality grades according to the distribution diagram, and defining a judgment rule; and performing interactive correction on the low-confidence region based on a rule to generate a final optimized fundus blood vessel segmentation result. And the final result is transmitted to a visual terminal for three-dimensional topology reconstruction. According to the method, the advantages of multi-modal data are integrated, and a more comprehensive fundus blood vessel segmentation result is formed.

The invention discloses a blood vessel plaque intelligent identification method and system based on optical coherence tomography, and relates to the technical field of medical image processing. Firstly, a three-dimensional blood vessel grid model is constructed through OCT volume data, vertex curvature parameters are quantified to generate a dynamic threshold template, the segmentation process is made to adapt to the local form of a blood vessel, and the problem of wrong segmentation of a traditional algorithm in a complex anatomical region is solved. Secondly, introducing a fractal dimension verification mechanism, quantitatively evaluating an initial segmentation result based on edge complexity, and when fractal features deviate from a preset threshold value, dynamically adjusting curvature weight parameters and iteratively optimizing segmentation, forming'segmentation-verification-correction 'closed-loop control, and remarkably suppressing artifact interference; and the finally output three-dimensional identification result comprises plaque space coordinates and morphological characteristics, and a visual decision basis is provided for clinic.

The invention relates to the technical field of image processing, and provides an OCT (Optical Coherence Tomography) image splicing method, which comprises the following steps: acquiring image pairs and matching point pairs corresponding to the image pairs, the image pairs being adjacent OCT images; calculating a homography matrix based on the matching point pairs so as to align the image pairs, and outputting preliminary aligned image pairs; constructing a fusion weight map, wherein the fusion weight map comprises a weight value of a pixel position and a region type; and according to the weight value and the region type, carrying out fusion splicing on the pixel positions so as to output a panoramic OCT image. According to the method, partition fusion is achieved by fusing the weight map, the problems of tissue dislocation and artifacts in OCT splicing are solved, and then the problem that the splicing effect of OCT image splicing is poor is solved.

The invention discloses a multi-stage loss optimization OCTA (Optical Coherence Tomography Angiography) image diagnosis method based on semi-supervised learning and knowledge distillation. The method comprises the following steps: (1) constructing a teacher-student model framework in combination with semi-supervised learning; (2) data set processing: randomly removing part of sample labels of the training set as label-free data; (3) training a teacher model by using the labeled data, then generating a pseudo label of non-labeled data through the teacher model, and only retaining a high-quality pseudo label meeting a confidence threshold; and (4) training a student model by using a multi-stage loss function, wherein the student model comprises supervision loss of label data, supervision loss of pseudo-label data and knowledge distillation loss. Dependence on annotation data is reduced through semi-supervised learning, the performance of the lightweight student model is improved through knowledge distillation, and the method is suitable for scenes with limited clinical resources.

The invention relates to the technical field of medical image processing and artificial intelligence, and discloses an artificial intelligence-based retinochoroid disease course structure change monitoring system, which comprises an image acquisition unit, a feature extraction unit, a lesion segmentation unit and the like. The image acquisition unit acquires retina optical coherence tomography sequence image data and fundus color image data; the feature extraction unit extracts a retina choroidal structure feature tensor through a three-dimensional convolutional neural network; the lesion segmentation unit outputs a lesion area probability distribution diagram by using a U-Net segmentation network; the time sequence alignment unit is used for registering the multi-time-point images to generate a displacement change matrix; the dynamic analysis unit extracts related indexes; an abnormal scoring unit constructs a disease course progress score; the decision grading unit outputs disease course stage classification labels; the multi-modal fusion unit fuses the multi-modal features; the report generation unit generates a structured disease course monitoring report. And favorable support is provided for diagnosis and treatment of ophthalmic diseases and illness state tracking.

The invention relates to the field of ulcerative colitis, and discloses a multi-parameter monitoring system for evaluating the intestinal barrier function of ulcerative colitis, which is used for realizing the goal of automatically adjusting a treatment scheme according to a monitoring result by constructing a closed-loop feedback treatment system. According to the invention, by designing the nanoprobe of which the surface is modified with a specific binding element and combining with a swallowing capsule endoscopy, real-time imaging and molecular level dynamic tracking of the intestinal barrier are realized, genetically engineered bacteria are constructed to quantify intestinal permeability abnormality and local inflammation level, and an intestinal barrier function damage score and a disease progress prediction result are output; individual monitoring is achieved through transfer learning, ultrasonic elastography, optical coherence tomography, wearable equipment for measuring intestinal electric field impedance spectroscopy and other technologies are adopted, an intestinal wall mechanics-electrophysiology composite parameter set is obtained, and the evaluation accuracy is improved.

Disclosed herein are systems and methods for compensating for a tilt of an intraocular lens (IOL) and systems and methods for adjusting the IOL. For example, one of the methods can comprise capturing one or more optical coherence tomography (OCT) images of an eye of a subject when the IOL is implanted within the eye of the subject. The method can also comprise generating a fixation target such that the fixation target is visible to the eye of the subject and moving the fixation target until a transverse plane of the IOL is perpendicular or substantially perpendicular to an optical axis of an ophthalmic system. The method can also comprise directing a laser beam generated by a laser of the ophthalmic system at the IOL.

The utility model relates to the technical field of laser welding, in particular to a laser welding system with an OCT (optical coherence tomography) online detection function, which comprises an OCT device, a laser processing system, an infrared sensor, a computer and a controller. The laser processing system is provided with a laser processing head, and the infrared sensor is used for acquiring a thermal induction temperature image so that the computer can generate a first control parameter; the OCT equipment is connected with the laser processing system through an optical fiber; the OCT equipment is used for providing a spectral interference fringe image for the computer; the computer is used for analyzing and processing the spectral interference fringe image to obtain a second control parameter; the controller is configured to control the laser processing head and adjust welding parameters in real time according to the first control parameter and the second control parameter; according to the laser welding system with the OCT online detection function, accurate welding is achieved, and various laser welding quality problems are effectively recognized.

The subject invention pertains to deep learning (DL) systems and methods for the binary classification of Alzheimer's Disease. Optical coherence tomography (OCT) generated reports were used, and the images were grouped into 3 different inputs: (1) an optic nerve head (ONH) model including a retinal nerve fiber layer (RNFL) thickness map, a RNFL deviation map, and an ONH-centered en face image; (2) a Macula model including a ganglion cell inner plexiform layer (GCIPL) thickness map, a GCIPL deviation map, a macular thickness map, and a macula-centered en face image; and (3) a General model including all images of (1) and (2). A fusion network is provided to analyze the plurality of images from a single eye for classification. The fusion network includes Feature Extraction, Feature Fusion, and Feature Reconstruction. Ensemble learning is provided to advantageously combine several baseline models to build a single but more powerful model.

A system and method for determining a difficult venous access of a patient. Logic processes meta data acquired by a vasculature assessment device coupled with the patient. The meta data, e.g., vessel diameter, vessel depth, vessel wall thickness, vessel wall elasticity, tissue elasticity, tissue profusion, blood flow rate, or hydration level. The logic further determines a difficult venous access by performing an algorithm on the meta data. The algorithm is defined utilizing machine learning techniques applied to an ongoing collection data sets acquired from a plurality of systems across a plurality of patients undergoing catheter insertion events. The data set may also include patient data such as weight, age, etc. The vasculature assessment device may include ultrasound imaging, infrared imaging, molecular imaging, Raman spectroscopy, or optical coherence tomography to acquire one or both of three-dimensional imaging data and the meta data.

Disclosed herein are systems and methods for compensating for a tilt of an intraocular lens (IOL) and systems and methods for adjusting the IOL. For example, one of the methods can comprise capturing one or more optical coherence tomography (OCT) images of an eye of a subject when the IOL is implanted within the eye of the subject. The method can also comprise generating a fixation target such that the fixation target is visible to the eye of the subject and moving the fixation target until a transverse plane of the IOL is perpendicular or substantially perpendicular to an optical axis of an ophthalmic system. The method can also comprise directing a laser beam generated by a laser of the ophthalmic system at the IOL.

Disclosed herein are systems and methods for compensating for a tilt of an intraocular lens (IOL) and systems and methods for adjusting the IOL. For example, one of the methods can comprise capturing one or more optical coherence tomography (OCT) images of an eye of a subject when the IOL is implanted within the eye of the subject. The method can also comprise generating a fixation target such that the fixation target is visible to the eye of the subject and moving the fixation target until a transverse plane of the IOL is perpendicular or substantially perpendicular to an optical axis of an ophthalmic system. The method can also comprise directing a laser beam generated by a laser of the ophthalmic system at the IOL.

A catheter rotary apparatus for OCT includes a rotary junction module and a catheter. The rotary junction module includes a body part including a through part to enable an optical fiber on a sample stage side of OCT system to pass at one end and an optical fiber on a catheter side to pass at the other end, a fiber optic rotary joint provided at one end on the sample stage side of OCT system of the body part and configured to connect the optical fiber on the sample stage side of OCT system and the optical fiber on the catheter side and a catheter. The catheter includes a female type optical connector connected to the male type optical connector, and a cap part clamped to the body part. The cap part includes an outer cap coupled to a through part formed in the body part, an inner cap inserted into the outer cap, and a fixed cap coupled to the female type optical connector and rotated when the female type optical connector is rotated.

System and methods for optical coherence tomography. The systems may include a source of optical radiation, an optical fiber, a detector, an interface medium, a mirror in the embedding medium, and a processor. The optical fiber may provide a common path for optical radiation reflected from a reference and a target. The detector may receive the optical radiation reflected from the reference and the target. The interface medium may be at the reference interface and in optical contact with the distal end of the optical fiber. The mirror may include a silicon die having a reflective coating. The processor may generate an image of the target based upon the optical radiation received by the detector.

The invention discloses a method for automatically measuring the minimum diameter of a fundus macular pore based on an OCT (Optical Coherence Tomography) image, and particularly relates to the technical field of medical image processing. The method comprises the following steps of: preparing data, acquiring a disclosed fundus macular pore OCT data set, and cutting image data, so that only part of a macular pore focus area is reserved in an image, and preparation is made for image processing; image processing, including image denoising, image binaryzation, image morphological operation and edge detection; the method comprises the steps that firstly, image denoising adopts a mode of superposition of Gaussian filtering in linear filtering and median filtering in nonlinear filtering, then a global threshold value is automatically sought by using a triangle method, binarization processing is carried out on the denoised image according to the threshold value, and an image only containing black and white is generated; removing a capsular cavity area in the image through image morphological operation processing; and finally carrying out edge detection.

The invention discloses a method and a system for detecting nonuniformity of internal components of transparent glass by adopting OCT (Optical Coherence Tomography). The method comprises the following steps: S1, obtaining a three-dimensional image in the glass through the OCT; and S2, carrying out fault analysis on the three-dimensional image in the glass, and detecting defects in the glass according to refractive index change caused by non-uniform components. By adopting the technical scheme of the invention, the defects of uneven components, bubbles and microcracks in the glass can be accurately positioned and identified, and the quality control level of transparent glass products can be favorably improved.

An optical coherence tomography (OCT) imaging tool including an optical waveguide having a proximal end and a distal end, at least a portion of the optical waveguide disposed at the distal end of the optical waveguide having an increased elasticity than a proximal portion of the optical waveguide; a sheath surrounding at least a portion of the optical waveguide; and an optical probe coupled to the optical waveguide, the optical probe including: an optical element coaxially aligned with a central axis of the distal end of the optical waveguide, the optical element being configured to rotate about the central axis and redirect light emitted by the optical waveguide toward a circumference of the optical probe from the central axis, and the focusing element being disposed within a housing.

The invention discloses a cell image segmentation method, and relates to the technical field of cell analysis, and the method comprises the following steps: S1, image acquisition; s2, processing optical artifacts generated by imaging of the phase contrast microscope; s3, processing interference of impurities and debris in the cell image; in the method, a phase contrast microscope and an optical coherence tomography microscope are combined to obtain a cell image, three-dimensional structure information of an OCT image is utilized to assist in correcting artifacts generated by imaging of the phase contrast microscope, and the artifacts are processed based on phase recovery and filtering and texture feature matching and repairing. According to the method, the interference of impurities and debris is removed by applying a diffusion and repair method based on a partial differential equation and a machine learning classification and reconstruction method, so that the cell image quality is effectively improved, the interference of artifacts and impurities on subsequent analysis is reduced, and a reliable image data basis is provided for cell image segmentation and cell morphology analysis.

The invention provides an eye fundus image intelligent enhancement method and system based on multi-modal image fusion. The method comprises the following steps of obtaining a color eye fundus photography CFP image and an optical coherence tomography OCT image and performing preprocessing; establishing an image space coordinate mapping relation for the preprocessed color fundus photography CFP image and the preprocessed optical coherence tomography OCT image, and performing feature space alignment; the first branch network structure and the second branch network structure of the multi-layer Transform feature fusion module are used for carrying out feature extraction and enhancement on the features of the processed color fundus photography CFP image and the features of the processed optical coherence tomography OCT image respectively, and the features of the color fundus photography CFP image and the features of the processed optical coherence tomography OCT image are fused; multi-modal fusion image features are obtained; according to the multi-modal fusion image features, a deep learning model is adopted to reconstruct an eye fundus image; and constructing an image enhancement model to obtain an enhanced fundus image.

The invention relates to the field of electrophysiological catheters, in particular to a mapping and ablation system capable of detecting injury depth, which is characterized in that a tail end functional area is arranged at the far end of a catheter, and an electrode, a positioning sensor and an optical probe are arranged in the tail end functional area; the electrode is used for mapping and ablation; the positioning sensor comprises a coil structure; the optical probe is used for performing optical scanning on the contacted tissue. The ablation unit is communicated with the electrode and provides ablation energy for the electrode; the positioning unit is communicated with the catheter and is used for displaying the position and form of the tail end functional area and recognizing the deviation and rotation direction of the tail end functional area; the electrophysiology mapping unit is communicated with the electrode and acquires an electrophysiology signal through the electrode; the optical detection unit is connected with the optical probe through an optical fiber and used for optical coherence tomography; the impedance detection unit is communicated with the electrodes, impedance information of surrounding tissue under different frequencies is collected through the electrodes, and then the frequency response coefficient of the position where each electrode is located is solved and used for recognizing whether the electrodes make contact with the tissue or not.

The invention discloses an optical coherence tomography device for optimizing aberration digital compensation and an imaging method, the device comprises an optical coherence tomography device and an image processing module, and the optical coherence tomography device comprises an illumination module, an interference module, an area array detection module and a synchronous control module. The imaging method comprises the following steps: setting device light source parameters according to coherent gating, and determining a sampling matching relation of the area array detection module according to a sampling theorem; selecting a frequency sweeping mode or a time domain mode, electrifying to activate a corresponding light source and a synchronous time sequence, and adjusting the position of a reference mirror; collecting a full-field interference sequence of the area-array camera, performing digital aberration compensation, performing compensation and denoising on volume data of different depths, and exporting a three-dimensional diffraction limit image; and outputting a three-dimensional tomographic image with transverse diffraction limit and axial micron-level resolution. According to the invention, the imaging resolution and the imaging speed of optical coherence tomography are improved under the conditions that the camera specification is reduced, the GPU dependence is reduced and the system cost is reduced.

The invention discloses a parallel imaging OCT (Optical Coherence Tomography) system based on a metasurface area array, which relates to the technical field of medical instruments, is small in size and can realize intraocular single-shot area array imaging and a three-dimensional position depth perception function by using metasurface and optical coherence tomography imaging information in a sample tissue with a limited size. According to the technical scheme, a light beam emitted by a laser is divided into two paths through a beam splitter, and the two paths enter a sample arm module and a reference arm module respectively; the sample arm module is a probe and comprises a multi-core optical fiber and a first metasurface; the reference arm module comprises a collimator, a motor and a right-angle reflector; the probe enters a sample tissue, a light beam is focused on the sample tissue and then is backscattered, the backscattered light beam reversely passes through the first metasurface, the multi-core optical fiber, the beam splitter, the second metasurface, the third lens, the grating and the focusing lens and then forms a spectral line beam on the CCD sensor, and the computer reads a signal from the CCD sensor and performs three-dimensional reconstruction imaging on the sample tissue.

According to an aspect of the present disclosure, a cart for optical coherence tomography includes a rotary catheter unit; a main body including a receiving member configured to receive the rotary catheter unit; a mobile unit coupled to a lower part of the main body and configured to move the main body on the ground; and a display unit connected to an upper part of the main body and configured to output information generated by the rotary catheter unit. Wherein the display unit is located inside at least two side surfaces of the main body.

A tunable laser assembly housed in a single enclosure and a method of control is described wherein the tunable laser, pump and semiconductor optical amplifier do not share a common optical axis but are all aligned to optical waveguides on an intervening planar lightwave circuit (PLC). Wavelength monitoring circuitry is included on the PLC to enable monitoring and control of the tunable laser center wavelength and optical bandwidth. The design of the PLC does not introduce perturbations into the swept-source laser output spectrum that would cause artifacts in imaging applications such as optical coherence tomography (OCT).

The invention discloses an optical coherence tomography optical path structure and a dispersion compensation method thereof. The light path structure comprises a coherent light source, a 2 * 2 optical fiber coupler, a reference light path, a sample light path, an equal-wave-number spectrograph and an upper computer; low-coherence broadband light emitted by the coherent light source is divided into reference light and sample light after passing through the 2 * 2 optical fiber coupler, the reference light and the sample light are sequentially transmitted in a reference light path and a sample light path, the reference light and the sample light are retroreflected through a sample and a reference mirror and are retroreflected to the 2 * 2 optical fiber coupler according to an original light path, interference is generated, and interference light beams are transmitted to the equal-wave-number spectrometer. Interference light beams are split to an upper computer according to equal wave number intervals, and a tomographic image of a sample is obtained through algorithm processing of the upper computer. By means of the structure, the existing dispersion loss problem is solved from the source, most dispersion generated by a light path is solved, other dispersion is eliminated by adding a dispersion compensating mirror made of optical glass materials with certain thickness in the light path through algorithm calculation, the algorithm is simple, convenient and fast, and the imaging speed is high.

The invention relates to the technical field of laser cleaning processing, and particularly discloses a real-time monitoring method for laser cleaning of a carbon fiber composite material. An optical coherence tomography (OCT) detection unit and a sensor module are innovatively adopted to form a real-time monitoring system, and according to the surface treatment requirement of the carbon fiber composite material, a temperature sensor in the sensor module is used for collecting a heat radiation signal of a laser irradiation area in real time, and the surface layer temperature of a base material during machining is monitored in real time; the distance between a machining head and a base material is dynamically tracked through a laser ranging module in the sensor module, the OCT detection unit obtains micron-sized surface topography characteristics through frequency domain interference signal analysis, and surface roughness parameters are synchronously calculated. The data of the three channels are fused through the edge calculation module and then fed back in real time through the displayer, and the temperature field, the roughness and the focal length are effectively monitored in the cleaning process. According to the method, damage to the base material due to factors such as laser ablation can be avoided, the operation time is effectively shortened, and the operation efficiency is improved.