19 results about "Neuroimaging" patented technology

This invention relates to the field of organic small molecule fluorescent probe technology, specifically to a neuron-specific dual-targeting fluorescent probe targeting the AChR of cholinergic neurons and its applications. The fluorescent probe, whose structure follows general formula I, is characterized by its dual-targeting structure, making it particularly suitable for the identification and labeling of cholinergic neurons. Furthermore, this fluorescent probe exhibits significant advantages in multiple application scenarios, such as cell imaging, protein and organelle labeling, tumor-specific recognition, and photodynamic therapy, with its potential application value in neuroimaging being particularly prominent. This fluorescent probe is expected to advance the development of neurobiology, disease diagnosis, and treatment methods, and has promising application prospects.

The invention discloses a mental disease typing method and system integrating DNA methylation and neuroimaging, and the method is a neuroimaging biological annotation method integrating DNA methylation and brain connection group data, and comprises the steps: recognizing brain network features related to a specific molecular phenotype in a whole brain range through a machine learning model; and mechanism-sensitive layering of the mental disorder heterogeneity group is realized. The method does not need to depend on a prior classification or hypothesis mechanism, can be suitable for different types of mental disorder people, provides technical support for exploring potential biological mechanisms and identifying targeted therapy groups, and has high generalizability and clinical application prospects.

The present disclosure provides technologies that allow reduced field of view or fast imaging with reduced image distortion. The first technique capitalizes on the benefit of reduced field of view imaging for full field of view coverage. The second technique allows achieves high resolution 3D images in a focused region. These techniques are expected to have applications for cancer imaging, neuro imaging, and other biomedical imaging areas.

An imaging system comprising: a light source configured to provide wavelength-swept emission of light; a sample delivery channel coupled to the light source and arranged to be coupled to an object to be imaged to direct light from the light source towards said object; a reference channel coupled to the light source for receiving light therefrom; a sample receiving channel arranged to be coupled to the object to be imaged for receiving sample light from the object; a detector coupled to the sample receiving channel for receiving sample light, and coupled to the reference channel for receiving reference light, wherein the detector is arranged to combine the received sample light with the reference light to provide a combined light signal comprising one or more components at a beat frequency between sample light and reference light; and a lock-in amplifier arranged to: (i) receive a detection signal based on the combined light signal and formed of one or more components at different frequencies, (ii) receive a selection signal at a selection frequency, and (iii) to provide one or more output signals indicative of a component of the detection signal at the selection frequency.

The disclosed system provides an integrated neuroimaging analytics platform for comprehensive preoperative neurosurgical planning, intraoperative neurosurgical guidance and post-operative assessment by processing multimodal MRI (structural, diffusion, functional, and angiography) and CT data. The platform performs detailed anatomical characterization by delineating tumor subregions (peritumoral edema, enhancing tumor, and necrotic core), segmenting brain tissues (gray matter, white matter, and CSF), and executing lobe, cortical / subcortical parcellation. Advanced 3D rendering visualizes tumors alongside critical white matter fibre tracts derived from diffusion MRI, while MRA data is used to segment cerebrovascular structures, and functional MRI analysis identifies eloquent cortices associated with motor, speech, and visual functions. All results are integrated within a user-friendly GUI featuring advanced multiplanar slicing and a smart brush for interactive mask editing, complemented by a speech-to-text engine for streamlined analytical reporting. This comprehensive approach facilitates precise and efficient surgical planning, thereby enhancing patient safety and improving clinical outcomes.

The invention relates to a living body capillary dynamic nerve imaging tracking method, system and device and a medium, and the method comprises the steps: collecting the continuous capillary image data of a living body tissue; performing blood vessel segmentation processing on the continuous capillary image data, and identifying a capillary network skeleton for motion analysis; based on the capillary network skeleton, calculating a motion vector of the segmented continuous capillary image data, and obtaining a motion track of red blood cells in the capillary; according to the motion trail, haemodynamic parameters including the flow velocity, the direction and the blood oxygen level are generated; synchronously acquiring local neural activity data of the continuous capillary image data under the same space-time coordinate system; and according to the haemodynamic parameters and the local neural activity data, generating a tracking result of the in-vivo microvascular haemodynamics and neural activity, so as to achieve the purpose of performing synchronous tracking and dynamic correlation analysis on the microvascular haemodynamics and neural activity in the in-vivo environment.

This application relates to the field of medical neuroimaging processing and computer-aided diagnosis technology, and discloses a method based on normal white matter. 18 An Alzheimer's Disease (AD) Auxiliary Assessment System Based on F-florbetapir Retention Features. This system includes a data acquisition module for acquiring multimodal brain imaging data of subjects; an image preprocessing and segmentation module for impurity removal and target localization of the image data; a feature extraction module for extracting image features from the processed images; and a joint assessment and prediction module for AD auxiliary assessment based on the extracted features, incorporating a subject performance characteristic model and a logistic regression system. This Alzheimer's Disease (AD) auxiliary assessment system can significantly improve the accuracy of early AD diagnosis, accurately predict the rate of cognitive decline, and dynamically monitor the effect of immunotherapy.

Neuroimaging and / or brain activity sensing machines, such as MEG and OPM machines use a helmet-like or head covering device that includes sensors for acquiring information from a participant's brain activity. The machine is operated while the participant undergoes tests, which can include a need for sight. People with glasses, therefore, need access to their glasses, but the glasses need to be non-ferromagnetic. In addition, due to the shape of the helmet-like objects and the need to have the sensors as close to the participant's head as possible, having glasses that include a contour that closely matches the shape of the helmet will improve the information obtained by the machine.

The invention discloses a depressive attack suicide risk prediction method and device based on a multi-modal neural image. The method belongs to the crossing field of medical artificial intelligence and neural image analysis, and a multi-level machine learning model is trained by extracting the brain multi-parameter structure-function coupling degree, so that the coupling relationship between the brain region structure and function of a depressive attack patient with suicide risk is visualized. The objective biomarker-structure function coupling degree is provided, clinical doctors are assisted in interviews and questionnaire survey, and besides, brain region changes of patients with suicide risks are found through neuroimaging, so that the doctors are helped to optimize diagnosis and subsequent treatment schemes.

This invention provides a magnetic resonance receiving device suitable for auditory stimulation of awake marmosets, relating to the field of receiving coil design for magnetic resonance imaging. It includes an animal bed, a head fixation assembly, and a body shell. The animal bed has a placement slot; the head fixation assembly includes a mandibular support and a head shell, the mandibular support being detachably disposed in the placement slot, the head shell being detachably disposed above the mandibular support, and the body shell being detachably disposed on the animal bed; the head shell contains multiple radio frequency coils; both the mandibular support and the two side walls of the head shell have through slots for inserting auditory stimulation tubing. This invention, through the integrated design of radio frequency coils, a head fixation assembly, and an auditory stimulation-compatible interface, enables high-quality neuroimaging and precise simultaneous auditory stimulation experiments in an ultra-high field magnetic resonance environment.

A neuroimaging-based approach to predict treatment response in mental disorders by acquiring and analysing brain PET dopamine measures from patients. The method uses a short, simplified protocol for [18F]FDOPA brain PET imaging adapted for clinical practice. Individual [18F]FDOPA brain PET data are then quantified with a fully-automated analysis pipeline to extract information on the dopamine function of the subject. This information coupled with clinical information is run through a prediction algorithm to identify those patients whose illness will not respond to conventional antipsychotics.

This invention discloses a collaborative optimization method and apparatus for three-dimensional tissue segmentation and registration of brain neural images. The method includes the following steps: Step S01. Constructing a segmentation and registration collaborative model, including a shared feature encoder, a segmentation path, and a registration path. The segmentation path is used to generate a segmentation probability distribution map, and the registration path is used to generate a deformation field. Step S02. Obtaining a training set of three-dimensional magnetic resonance imaging (MRI) images of the brain. Step S03. Collaboratively training the segmentation and registration collaborative model according to a multi-task collaborative loss function. The loss function includes segmentation loss, registration loss, and a collaborative regularization term. The collaborative regularization term modulates the deformation field gradient penalty term by using a multi-scale boundary weight map and tissue-specific mechanical weights. Step S04. Receiving the image pairs to be registered in real time and inputting them into the trained segmentation and registration collaborative model to obtain the registration result. This invention can significantly improve computational efficiency while ensuring segmentation and registration accuracy.

In an embodiment, a neuroimager alignment and coupling evaluation (NACE) system, includes a neuroimaging device; a fiducial affixed to the neuroimaging device; an imaging device; and an augmented reality (AR) module coupled to the imaging device and configured to provide alignment data for the neuroimaging device by tracking facial or cranial landmarks and the fiducial.

A method of preparing a neuroimaging system for neuroimaging and analysis of a subject's brain tissue, the neuroimaging system comprising a plurality of optical elements, wherein each optical element comprises one of: (i) a light source for emitting light towards the subject's brain tissue, or (ii) a light detector for detecting scattered light from the subject's brain tissue, the method comprising: placing optical elements on the subject's scalp to provide at least one source-detector pair where a light source on the subject's scalp is arranged to emit light towards the subject's brain tissue and a detector on the subject's scalp is arranged to detect scattered light from the subject's brain tissue which was emitted from that light source; wherein placing an optical element on the subject's scalp comprises: first, arranging said optical element at a selected location on the subject's scalp for providing at least one source-detector pair; and then, performing an iterative optical element arrangement adjustment process comprising: obtaining a measurement signal indicative of a goodness of fit for said optical element as arranged on the subject's scalp; and re-arranging said optical element at, or proximal to, the selected location on the subject's scalp based on the indication of goodness of fit for said optical element; wherein said iterative optical element arrangement adjustment process is repeated until a said measurement signal indicates a goodness of fit for said optical element which satisfies a threshold criterion.

A method for ventriculostomy of the cavity of the anterior horn of the lateral ventricle in children, characterized by the fact that a calculation is carried out before the start of operative correction, based on the data of preliminary neuroimaging of the brain in the frontal and sagittal planes, while aligning the obtained images along the coordinate axes, the first side in determining the key point is selected in the projection of the widest part of the ventricular cavity, retreating from the coronary suture to the ventral side from 0 mm to 10 mm; the second side in determining the key point is selected in the frontal plane in the projection of the widest cavity of the anterior horn of the lateral ventricle of the brain, from the side of catheter placement, its maximum width is determined, the final result obtained is divided in half, the results of the two sides for determining the key point are transferred to the cranial vault;intraoperatively, a ventricular catheter is inserted through the key point parallel to the sagittal suture, and its insertion tip is directed to the imaginary biauricular line.

The application provides a free-moving mouse neural imaging method and device based on visual servoing, and relates to the technical fields of neural imaging and optical sensor, and the method comprises the following steps: acquiring the space section line data of a mouse head marker by synchronously scanning the marker with at least two line lasers installed at the end of a tracking mechanism; solving the rotation component and the translation component of the marker step by step according to the space section line data, and combining to obtain a six-degree-of-freedom pose matrix of the marker relative to the end of the tracking mechanism; controlling the movement of the tracking mechanism according to the six-degree-of-freedom pose matrix, so that an imaging system installed at the end of the tracking mechanism follows the marker; in the process of the movement of the tracking mechanism, a fluorescent image sequence of the mouse brain is collected by the imaging system, and non-rigid displacement correction and light intensity equalization correction are performed. The application realizes high-precision, high-throughput, non-contact and long-term stable imaging of the neural activity of a free-moving mouse, and is compatible with various microscopic imaging paradigms.

The invention relates to the technical field of neuro-endoscope transnasal approach preoperative planning, provides a neuro-endoscope transnasal approach preoperative planning method and system based on multi-modal image fusion, and solves the problem that a planning path safety boundary is difficult to accurately control. The method comprises the following steps: acquiring intracranial nerve imaging, angiography and distance evaluation data of a patient; fusing the two types of imaging data by adopting a multi-modal image fusion algorithm to obtain an initial three-dimensional fusion image, performing virtual ultrasonic scanning simulation on the anatomical structure based on a preset acoustic tissue characteristic model to generate acoustic characteristic data, and fusing the acoustic characteristic data with the initial three-dimensional fusion image to obtain a target three-dimensional fusion image; on the basis of the target three-dimensional fusion image, the preliminary planning path is adjusted in combination with a preset avoidance rule and a protection strategy, a preoperative planning scheme is output, multi-modal accurate fusion of the nerve nuclei and the blood vessels is achieved, and safe and accurate path planning support matched with a preoperative scene is provided for the neuroendoscopic nasal approach surgery.

The present invention relates to a head elevation and support device, in particular a head elevation and support device for use with a nuclear magnetic resonance (NMR) device. The head elevation and support device being shaped and configured to elevate and support a head of a patient for neuroimaging by a NMR medical device.

The application discloses a biological feature analysis method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an electroencephalogram signal and a cerebral oximetry signal of a target; performing feature extraction on the electroencephalogram signal to obtain an electroencephalogram feature, and performing feature extraction on the cerebral oximetry signal to obtain a cerebral oximetry feature; and analyzing the electroencephalogram feature and the cerebral oximetry feature to obtain a biological feature, wherein the biological feature comprises a neurovascular coupling relationship between the electroencephalogram signal and the cerebral oximetry signal and a comprehensive brain function connection feature of the target. The technical scheme of the embodiment of the application is aimed at the electroencephalogram signal and the cerebral oximetry signal collected by a multi-modal fNIRS-EEG neuroimaging acquisition technology, and the electroencephalogram signal and the cerebral oximetry signal are respectively subjected to feature extraction, and the biological feature obtained by analyzing the electroencephalogram feature and the cerebral oximetry feature has more complete information in time and space, thereby providing better diagnosis and treatment basis for medical staff.