48 results about "Imaging modalities" patented technology

A method is provided for generating and / or displaying a dynamic tooth chart In some cases, the method can include receiving dataset(s) associated with a patient. Each dataset comprises data corresponding to an imaging modality of a plurality of imaging modalities and provides information on a dentition of the patient. The datasets are processed to generate, for each dataset, one or more tooth portions. Each tooth portion comprises an image of one or more teeth of the patient. The one or more tooth portions are arranged into a dental chart. A visualization of the dental chart of the patient is generated and provided to a user device for presentation in a user interface. In some cases, a method can include determining one or more chart annotations can by performing a shape analysis, a teeth arrangement analysis, and / or a material analysis on 3D dental model(s) and / or 2D images of the patient's jaw.

A deployment system for accurate placement of localization tags within biological tissue is disclosed. The system comprises a catheter hub with sheath, a stylet, and a loader. The catheter hub provides an interface for system components, while the flexible sheath allows navigation to target sites. The stylet, operable in multiple positions, guides the sheath and assists in tag deployment. The loader houses the localization tag and acts as a safety spacer during deployment. The system is compatible with endoscopes and various imaging modalities, offering improved accuracy and efficiency over traditional wire localization techniques. The localization tags may be passive or active, with potential for advanced functionalities such as biosensing or drug delivery. This minimally invasive system finds applications in tumor marking, lymph node localization, and targeted therapy delivery across multiple medical specialties.

The present disclosure provides a system and method for automated monitoring, quantification, and control of plant health from micro and macro scales using optical sensing and imaging modalities, environmental sensing, data analysis, image processing, and machine learning. Intelligent feedback control of plant health employed in the system reacts in real-time to changes in plant health to enable precision agriculture applications like intelligent irrigation or determination of optimal fertigation parameters. In turn, the system results in improved agricultural outcomes such as increased fruit production or unique flavor profiles. The system further provides a means for automated and non-invasive testing of novel treatments for disease or adverse conditions, or to improve crop yields.

A compact confocal scanning laser ophthalmoscope comprising a MEMS scan mirror with a compact scan head, for use with small animal subjects. The scan head is connected to the source, detector and control electronics by flexible optical and electrical umbilicals and includes a zoom lens to provide both a wide field of view and high resolution imaging of the retina using a range of imaging modalities.

A method is provided for generating and / or displaying a multimodal timelapse visualization. In some cases, the method can include identifying a plurality of records associated with a dental arch of a patient. Each record corresponds to a point in time and to an imaging modality of a plurality of imaging modalities. Based on processing of at least one record, a clinical finding is determined for the patient. A primary imaging modality is determined based at least in part on the clinical finding. At least a subset of the plurality of records is normalized. A timelapse visualization representing the normalized subset of records displayed in chronological order of the plurality of points in time is generated. The timelapse visualization is provided to a user device for presentation in a user interface of the user device.

A heat transfer device for circulating a heat transfer medium therein, and a method for protecting the esophagus and other areas of the body during ablation or thermogenic procedures performed nearby. The device typically includes an elongated outer shaft and an elongated inner shaft positioned within an outflow shaft. A distal end includes a fluid opening allowing fluid communication between the outer and inner shafts. A heat-insulating member, such as a sleeve, is positioned along a portion of the inner surface of the outer shaft, thereby defining the insulated and active heat transfer portions of the heat transfer device. The outer shaft may also include radiopaque or other imaging materials, enabling the device to be detected using imaging methods. During ablation procedures, cooling fluid circulates through the device to protect the esophagus from damage.

A multispectral photonic imaging system and associated methods are disclosed for classifying wound tissue and generating customized therapeutic wound dressings. The system employs wavelength-specific optical sources and integrated image sensors to capture multispectral reflectance data from a wound, enabling computational classification of distinct tissue types such as granulation, slough, and necrosis. A three-dimensional (3D) digital model of the wound is constructed using spatial data from depth sensors. The classified 3D wound model facilitates automated design of patient-specific dressings, featuring heterogeneous regions tailored with therapeutic compounds like antimicrobial agents, analgesics, collagen scaffolds, and hydrogel matrices precisely aligned to corresponding tissue classifications. Additional imaging modalities, including thermal and ultrasound sensors, can be integrated to enhance classification accuracy and inform targeted therapeutic placement, providing a comprehensive and personalized approach to wound management for medical and veterinary applications.

The present disclosure in some aspects relates to methods for assessing multi-modal in situ transcriptomics by combining microscopy and sequencing technologies and methods. In some aspects, the methods provided herein involve analyzing one or more analyte panels in a sample using a first imaging modality or set of imaging modalities. Based on said analysis, a different analyte panel and / or one or more different imaging modalities can be selected for subsequent analysis.

A computer-implemented method for multi-modality medical image clinical workflow guidance comprises a step of receiving a user input (306-4) in relation to a first medical image data set (306-2) acquired by means of a first medical imaging modality (304-A). By means of a clinical-concept-to-medical-image linking algorithm (314), the received user input (306-4) is assessed in view of at least one second medical image data set (308-1) acquired by means of at least one second medical imaging modality (304-B). An indication of a clinical workflow guidance in relation to the at least one second medical image data set (308-1) is output.

This disclosure provides a method for matching collaterals from different imaging modalities. Collaterals detected from a series of intravascular images can be matched with collaterals detected from extravascular images. Matching pairs can be determined based on an initially identified reference pair and then based on techniques that take into account characteristics of the collaterals, such as diameter, orientation, relative size, and / or relative order.

The disclosure relates to an apparatus and method for imaging fluid-carrying tubulars, such as pipelines and downhole tubing, using real-time adaptive ultrasonic imaging and multiple imaging modalities for a single transducer array. An imaging tool dynamically adjusts beamforming parameters based on the surface characteristics and geometry of an inspected target, to compensate for differences between the actual and expected location of a transducer array relative to the target surface. An imaging tool and method is disclosed that employs multiple transmit and receive cycles to capture various features such as cracks, metal loss, and geometry using a single transducer array, enhancing defect detection and characterization. A tool and method are described for generating image data by compensating for the directionality of a transducer element or array. Further, a method for efficiently ray tracing a region of interest based on a measure of received energy is disclosed.

The application discloses a kind of fast high-resolution imaging methods based on vortex electromagnetic wave, which constructs the two-dimensional imaging model of pitch angle and azimuth angle based on concentric circular ring array, realizes low-rank decomposition to the received echo and observation matrix by means of spherical harmonics function, introduces orthogonal matching pursuit algorithm to the scattering point in observation plane for target reconstruction, so as to realize the two-dimensional joint imaging of radar target pitch angle and azimuth angle.The imaging mode of joint OMP algorithm and spherical harmonic decomposition proposed in the application can realize higher imaging resolution compared with the traditional generalized inverse solution mode, while greatly reducing the operation amount of imaging process, effectively saving calculation time.

This invention discloses a multi-channel fusion automatic matching method and system for pathological images, used in the field of medical image matching to overcome the technical challenge of high-precision matching of pathological images, and to meet the clinical needs of cancer auxiliary diagnosis by locating local common regions in pathological images. First, multiple single-modal image matching channels are created by normalizing image modalities. Then, image matching is performed in each channel, including extracting feature points, constructing feature vectors, and determining matching features. Next, based on the consistency of the mapping relationship of the matching features, the multi-channel matching features are fused to determine the matching result. Finally, the highly consistent matching result is used to assist in the precise clinical location of local common regions in pathological images. The pathological image matching method and apparatus provided by this invention avoids the interference of modal differences in pathological image matching by normalizing image modalities, and enhances the consistency of matching results by fusing multi-channel matching features, avoiding erroneous matching and improving matching accuracy.

This invention discloses a method and system for grading myopic macular degeneration (ATN) based on multimodal medical imaging. The system includes an image acquisition module for acquiring multimodal retinal images to be graded; a preprocessing module for preprocessing the multimodal images to obtain image sequences that meet preset grading requirements; and a grading module for inputting the image sequences into a pre-stored multimodal multi-task grading model. The model performs feature extraction, multimodal fusion, and multi-task classification on the image sequences, outputting a lesion grade prediction result for each grading task. This invention significantly improves the model's sensitivity to pathological regions by performing pixel-level segmentation of the input images and locating key anatomical structures. In subsequent steps, spatial weighting is applied to CFP image modalities, and specific regions of OCT and OCTA are enhanced, effectively improving the accuracy and robustness of lesion diagnosis and localization.

This disclosure relates to a training method for a data generation model, a method for generating an acoustic parameter field, and an apparatus. The method includes: configuring a data generation model according to the imaging modalities corresponding to a training sample set; for each training modal image, performing style encoding through a corresponding style encoder to obtain training style features, and performing content encoding through a shared content encoder to obtain training content features; performing modal decoding through a modal decoder based on the corresponding training content features and training style features to obtain a predicted reconstructed image; performing cross-modal fusion processing on multiple training content features, and inputting them into an acoustic decoder for acoustic decoding to obtain a predicted acoustic parameter field; and completing iterative training of the data generation model based on the differences between each predicted reconstructed image and the corresponding training modal image. This embodiment focuses on the inherent feature information of the acoustic parameter field contained in different modal images, ensuring the accuracy and reliability of the generated acoustic parameter field.

This invention relates to the field of display screen inspection technology, specifically to a dynamic detection method for pixel-level defects in display screens based on multispectral imaging. The method includes the following steps: employing multi-band parallel imaging to acquire high-resolution images of multiple fixed bands during dynamic display; performing filtered edge tracking and blurred region interpolation compensation, and using dynamic threshold updates to segment individual physical pixels in dynamic scenes; extracting three multi-dimensional features of pixels—multi-band light intensity, band correlation, and spatiotemporal dynamics—and using multi-band cross-validation to identify and classify pixel-level defects in the display screen, outputting the identification and classification data; through the above methods, dynamic adaptation and segmentation accuracy are improved, meeting the quality control requirements of large-scale production of high-resolution, high-refresh-rate display screens.

The application discloses a multi-modal medical image intelligent fusion diagnosis process, which comprises the following core process steps: S1, multi-modal image data acquisition and preprocessing, collecting original data of at least two kinds of clinically commonly used image modalities, performing format standardization, artifact suppression, gray scale normalization and quality screening processing on the original data, and obtaining standardized image data; S2, cross-modal adaptive registration and fusion integrated processing, based on a cross-modal registration and fusion integrated network, synchronously realizing spatial alignment and preliminary feature fusion of the standardized image data, and generating an aligned feature map; and S3, layered feature extraction, adopting a differentiated feature extraction architecture adapted to different modal imaging characteristics.The application realizes the transparency and traceability of the diagnosis process through feature contribution degree visualization and diagnosis logic tracing, enables a clinician to clearly understand the diagnosis basis, meets the requirement of clinical diagnosis and treatment on explainability, significantly improves the trust degree of the clinician on the diagnosis result, and reduces the clinical application threshold.

The application discloses a kind of high-level semantic guide low-level controlled alignment multi-modal three-dimensional target detection method, system and vehicle, introduce Cross Mamba cross-modal global fusion mechanism on high-level BEV feature, realize continuous stable cross-modal semantic propagation in BEV grid by sharing hidden state.The scene-level consistent semantics of high-level fusion feature is used as a constraint condition, and small-range controllable spatial correction is performed on low-level multi-scale features, and neighborhood constraint is applied to the offset amplitude, and the laser radar BEV feature is used as a geometric anchor to keep the sampling position unchanged or only perform limited fine-tuning.After controlled alignment, scale guide features and aligned modal features are used to predict dynamic fusion weights, so that the image modality occupies a higher weight in the semantic reliable area, and the laser radar modality occupies a higher weight in the geometric stable area;At the same time, cross-scale state space modeling is performed on multi-scale fusion features, so that global information and local information between different scales can be bidirectionally propagated and cooperatively integrated.

The application discloses a two-dimensional code subcutaneous microchip, which comprises a substrate and at least two pattern elements arranged on the substrate, the pattern elements are arranged to be recognizable by an ultrasonic-based imaging device and are converted into black elements and white elements of a corresponding two-dimensional code. The application also provides a manufacturing method of the two-dimensional code subcutaneous microchip, after selecting an ultrasonic-based imaging mode, the material and structure of the microchip are selected according to the imaging mode, the size of each pattern element of the microchip is determined, and finally the microchip is manufactured. The microchip of the application is applied in personal identification and authentication, can be implanted under the skin of a person, and is recognizable by an ultrasonic-based imaging device. The application can be applied in various identity identification and authentication, is convenient to use, and will not be forgotten, misplaced or lost, and compared with biological feature identification based on exposure or physical entity token identification, can provide better privacy and security.

The application discloses a kind of human peripheral blood vessel photoacoustic three-dimensional imaging device and imaging method thereof, belong to blood vessel imaging field.The application provides detailed blood vessel structure and blood flow dynamic information by high resolution and functional monitoring ability of photoacoustic imaging, promote early identification and treatment effect evaluation to common pathological changes such as diabetic foot and peripheral arterial disease;Meanwhile, the application adopts mechanical system, and the detection front end of higher quality can be carried and stably operated, to obtain better photoacoustic imaging result;The application has highly stable precision scanning imaging mode, and various imaging modes are convenient for clinical application;Through the arrangement of imaging tank and its lifting structure, it is ensured that the switching of imaging mode can be applied in limited space, so as to be suitable for gantry type three-dimensional mobile device layout.The application is expected to promote the portability of equipment, reduce equipment development cost, be widely applied in clinical practice and community medical treatment, and improve disease management level.

A system for automated tumor margin determination in radiological images, comprising: an image acquisition interface configured to receive radiological image data from one or more imaging modalities; a preprocessing unit operationally coupled to the image acquisition interface and configured to perform intensity normalization, spatial resampling, and noise reduction on the received image data to generate standardized image inputs; a feature extraction unit comprising a plurality of convolutional layers arranged in a hierarchical structure and configured to extract spatial features of different orders of magnitude from the standardized image inputs;a transformer coding unit operationally coupled to the feature extraction unit and configured to generate context-sensitive feature representations by applying self-attention operations over spatial areas of the extracted features; a fusion unit operationally coupled to both the feature extraction unit and the transformer coding unit and configured to combine features derived from convolutions and context representations derived from transformers into a unified feature map; a decoding unit operationally coupled to the fusion unit and configured to generate a segmentation map corresponding to the tumor regions by incrementally increasing and reconstructing the spatial resolution; a boundary refinement unit configured to improve the delineation of tumor margins in the segmentation map;a processing unit that is operationally coupled with the preprocessing unit, the feature extraction unit, the transformer coding unit, the fusion unit, the decoding unit, and the boundary refinement unit, wherein the processing unit executes instructions stored in a memory unit to perform automated tumor boundary delineation; and a display interface configured to overlay the delineated tumor boundaries onto the radiological image data.

Systems, methods and programs including machine learning techniques which can predict a spectral image directly from an optical image of a patient's tissue sample using a first model. There may be different first models for different cancers. Each first model may be trained by using a plurality of pairs of images from different samples, respectively, where each image in a respective pair may be obtained via different imaging modalities. The systems, methods and programs may also include machine learning techniques which can predict cancer labels from the predicted spectral image using a second model. There may be different second models for different cancers. Each second model may be trained using multiple spectral images and corresponding manually input cancer labels.

This invention specifically relates to a single-exposure compressed imaging reconstruction method and system that integrates pre-trained language models, solving the problem that existing technologies can only decode a single imaging modality. It employs a model framework of "physical constraints-semantic guidance-sparse controlled diffusion," uniformly mapping cross-modal compressed data to align the data stream. On one hand, it utilizes a lightweight mask-gated constraint feature extraction module to extract high-fidelity underlying physical features; on the other hand, it cascades a pre-trained multimodal large language model to generate a global semantic representation. In the controlled diffusion large model denoising and reconstruction stage, an asymmetric sparse controlled DiT architecture is used to solve the problem of easily losing high-frequency details, and computational redundancy is significantly reduced by decreasing the number of controllable modules and layers. Through this hardware-software co-design, 3D positional encoding mechanism, and text prompt word design, a single model can adaptively reconstruct high-precision images with multiple imaging modalities and compression rates.

The application discloses a triage method and system, an image cloud server, a front-end machine and an image device, and relates to the technical field of medical treatment. After the image cloud server receives registration information of an object, the image cloud server can generate triage information based on the registration information. The triage information comprises a target image device for imaging the object and the registration information of the object. The registration information comprises basic information and an imaging mode. The front-end machine can issue the basic information of the object to the target image device based on the triage information, so that the target image device can image the object based on the basic information and obtain medical images. The target image device can send the medical images to the front-end machine, so that the front-end machine can upload the medical images to the image cloud server. In this way, on the one hand, the triage efficiency and accuracy are improved, and the efficiency of image examination is improved, without manual triage. On the other hand, the whole image examination process from information registration to imaging is automated, and the efficiency of image examination is improved.

The disclosure provides a unified system and method for analyzing 3D medical images through probabilistic masking, multimodal embedding generation, anomaly detection, and reinforcement learning-based refinement. The methods comprise applying ailment-aware probabilistic masking to 3D medical scans using prior distributions of known abnormalities to retain diagnostically relevant voxel regions. The masked scans are encoded into latent vectors using a vision transformer encoder, while associated textual medical reports are encoded using a language model; both are mapped into a shared embedding space. Anomaly detection is performed through (1) a temporal comparison method based on differences in patient embeddings across time, and (2) a similarity-based method comparing current embeddings to a database of known abnormal cases using cosine similarity. Reinforcement learning is applied to refine embeddings using human expert feedback, including corrected annotations and textual clarifications, allowing dynamic adjustment of thresholds and encoder parameters. This adaptive framework supports efficient, scalable, and accurate medical diagnosis across a variety of imaging modalities.

Methods and systems are provided to enable multiple imaging modalities with a single camera head. The camera head may include a two chip or a three chip system capable of measuring different wavelengths of light to generate different images. The light source in the system can adjust the output spectra, by using a plurality of illuminants and filters, and measurements from different light channels on one or more images sensors can be used to generate white light images, fluorescence image, perfusion images, fluorescein images, and the like.

Methods and systems are provided to enable multiple imaging modalities with a single camera head. The camera head may include a single chip system capable of measuring different wavelengths of light on different regions of the same image sensor to generate different images. The light source in the system can adjust the output spectra by using a plurality of illuminants and filters, and measurements from different light channels from different regions of the image sensor can be used to generate white light images, fluorescence image, perfusion images, fluorescein images, and the like.

A method of reconstructing the position of a source using a gamma camera. The gamma camera combines two imaging modalities: a coded mask imaging modality and a Compton imaging modality. The method comprises the selection of at least one isotope, the reconstruction being carried out according to a Bayesian probabilistic approach, taking into account each selected isotope.