111 results about "Nucleus" patented technology

The present invention involves a system and methods for nerve testing during anterior surgery, including but not limited to anterior total disc replacement surgery, nucleus replacement, and interbody fusion.

A method of segmentation of cell nuclei is described that uses an active contours approach based on a Viterbi search algorithm. Also disclosed is an initialisation technique that maximises the probability of a correct segmentation. The invention also includes a method to classify cell nuclei according to the difficulty of correct segmentation. Nuclei that are difficult to segment can be rejected to minimise the probability of false positives. The probability of false positives can be driven close to 0%.

The invention discloses a leukocyte nucleus and cytoplasm automatic segmentation method and a leukocyte nucleus and cytoplasm automatic segmentation system based on deep learning. The leukocyte nucleus and cytoplasm automatic segmentation method comprises the steps of: constructing a U-shaped neural network segmentation model, wherein the U-shaped neural network segmentation model comprises an encoder and a decoder, the encoder adopts an improved neural network structure for feature extraction, the decoder recovers details and spatial information of an image through up-sampling, and the encoder and the decoder adopt jump connection to supplement underlying information lost in the pooling process; training the U-shaped neural network segmentation model by adopting a leukocyte training set,setting a learning rate by taking leukocyte verification set loss as a monitoring index, and adjusting the learning rate when the monitoring index is not changed; and segmenting a leukocyte test set by adopting the trained U-shaped neural network segmentation model, and acquiring a segmentation result of cell nucleus and cytoplasm according to the classification probability of each pixel point ofa to-be-segmented image. Through adopting the improved U-shaped neural network segmentation model, morphological information of leukocyte nucleuses and cytoplasm can be rapidly obtained, and automaticsemantic segmentation of leukocyte nucleuses and cytoplasm is realized.

The invention relates to an HCC pathological image-oriented cell nucleus segmentation and classification method. The method comprises the steps of reading an original HCC image; performing k-means clustering on the image to obtain segmented cell nucleuses; performing refinement on the segmented cell nucleuses by using morphological operation, performing registration in three aspects, and performing calculation through four similarity parameters together with a cell nucleus shape library manually selected by a pathologist to obtain a cell nucleus shape feature matrix; according to the registered cell nucleuses, calculating cell nucleus boundary characteristics to obtain a cell nucleus boundary characteristic matrix; and fusing the cell nucleus shape feature matrix with the cell nucleus boundary characteristic matrix, and performing classification in a random forest classifier to obtain a result. The cell nucleuses are segmented by using the k-means clustering and the morphological operation; and the cell nucleuses are classified and identified through the proposed shape and boundary characteristics, so that the classification accuracy of each type of cell nucleuses is improved, theconditions of more cells are considered, and higher pertinence is achieved.

The invention provides an epileptic intracranial electroencephalography signal warning method based on a deep convolutional attention network. According to the method, through acquiring an intracranial electroencephalography (iEEG) signal at an ANT (Anterior Nucleus of the Thalamus) of an epilepsy patient for analysis, extracting and fusing a multi-scale time sequence characteristic and a multi-spectrum characteristic of the iEEG signal, simultaneously adopting an attention mechanism, and concerning the most significant features of the iEEG signal in an epileptic seizure period, the warning accuracy of the network is obviously improved. In one embodiment of the invention, verification is carried out on an iEEG signal data set containing five epilepsy patients, the average epilepsy warning accuracy (Sensitivity, Sn) of a single patient can reach 95.0%, the false predicting rate (FPR) per hour is less than 0.15, the warning effect and the model generalization ability are superior to those of an existing epilepsy warning method, accurate and rapid warning of epilepsy is realized, and thus, the method is of great significance in diagnosis and nerve regulation on clinical epilepsy diseases.

The invention provides a chemical heredity epilepsy persistent state disease animal model and a construction method and application thereof. The epilepsy persistent state disease animal model is a mouse brain kernel group (a hippocampus CA1 region and a thalamus anterior nucleus VA region of a model I); injecting a brain stereotaxic virus (a chemical genetic virus rAAV-CaMKIIa-hM3D (Gq)-mCherry-WPREs-pA) in an apricot kernel BLA region and a thalamus anterior nucleus VA region on the outer side of a substrate of the model II, and embedding an electrode array in a mouse hippocampus CA3 region;after the mouse is recovered for one week, a metabolite CNO of clozapine is injected into the abdominal cavity so that the CNO is combined with a virus expression receptor, neurons are activated to induce epileptic persistent state attack, and the epilepsy persistent state disease animal model is obtained through behavioral observation and in-vivo multichannel local field potential recording judgment. The epilepsy persistent state disease animal model constructed by the method is stable in seizure duration, high in success rate, low in death rate and good in repeatability, and has important significance in researching the origin and formation mechanism of epilepsy persistent state, and screening and mechanism of drug-resistant epilepsy persistent state drugs.

Systems and methods are provided for neurostimulation timed relative to respiratory activity. Neurostimulation may be delivered to the spinal cord, the vagus nerve, and/or branches of the vegus nerve to provide therapeutic outcomes by controlling or adjusting stimulation based on pulmonary activity. In particular, the systems and methods use a detecting device to detect respiratory activity over time. Specific points in the respiratory signal are identified where central autonomic nuclei may be more receptive to afferent input and a stimulator is instructed to provide neurostimulation to at least one auricular branch of a vagus nerve, or to a cervical branch of the vagus nerve, or to a spinal cord of the subject. In this regard, the neurostimulation is advantageously correlated to the detected respiratory activity providing improved therapeutic outcomes.

The invention discloses a wireless wearable neural signal detectiondevice and system. The device includes a flexible microelectrode array and a wearable detector, wherein the flexible microelectrode array can be implanted into nervous nuclei in the brain, and is applied to synchronous detection of neural electrophysiological signals and neural electrochemical signals, the wearable detector is usedfor receiving the neural electrophysiological signals and neural electrochemical signals which are output by the flexible microelectrode array, performing conditioning analysis, analog-to-digital conversion and compression on the neural electrophysiological signals and neural electrochemical signals and sending the compressed signals in a wireless mode. Unrestricted free movement and behavior ofanimals are facilitated in the research, and the problem of difficult movement of the animals duringcontinuous monitor of neural information in the research of behavioral neural mechanisms of the animals can besolved.

The invention relates to a leukocyte extraction and classification method based on an improved K-means and a convolutional neural network. The method comprises the steps of firstly, selecting an initial clustering center according to cell image gray level distribution, and clustering all pixels of an image initially according to the principle of proximity; then, improving the Euclidean distance ofthe FWSA-KM algorithm; before the extraction of leukocytes, carrying out the color space decomposition firstly, and carrying out the cell nucleus and cytoplasm extraction by adopting a color component beneficial to leukocyte segmentation and an improved K-means algorithm; separating a complex adhesion part by adopting a watershed algorithm; and finally, performing classification based on the convolutional neural network. According to the method, the leukocyte nucleus segmentation precision and the cytoplasm segmentation precision are 95.81% and 91.28% respectively, and compared with a traditional segmentation method, the precisions are greatly improved, the classification accuracy can reach 98.96% at most, the classification average time is 0.39 s, and compared with an existing leukocyteclassification algorithm, the CNN classification method not only has obvious advantages, but also has the great improvement space.

The invention discloses a universal multi-angle probing curette for preventing residual nucleus polposus under spinal endoscopy, and belongs to the field of surgical instruments. The probing curette comprises a fixed handle, a connecting block and a sheath rod, and further comprises a probing curette head and a flexion and extension mechanism; the probing curette head is hingedly arranged at one end of the sheath rod; the flexion and extension mechanism comprises a first drawing wire and a first movable handle, the first movable handle is hinged with the fixed handle, one end of the first drawing wire is connected to the first movable handle, and the other end of the first drawing wire passes through the connecting block and the sheath rod in sequence and is connected to the probing curette head; and the probing curette also comprises a universal adjusting mechanism. According to the present invention, the probing curette is provided with the flexion and extension mechanism, and the scraping of the nucleus pulposus can be completed by the action of tightening the first movable handle without scraping back and forth, so as to avoid inserting too deeply to damage normal tissue; and the probing curette is provided with the universal adjusting mechanism, the adjustment of scraping direction of the probing curette head by the action of tightening a second movable handle, and one-hand operation can be realized during the adjustment.

The invention relates to an intelligent nerve pressure reduction system, which comprises an electroencephalogram collection module used for monitoring electroencephalogram signals; a physiological index collection module used for monitoring blood pressure and heart rate; an analysis control module used for controlling the first stimulation module and the second stimulation module to work independently or simultaneously according to the monitored electroencephalogram signal, blood pressure and heart rate, and controlling the working modes of the first stimulation module and the second stimulation module; a first stimulation module used for stimulating the outer side area of the end abdomen of the medulla oblongata head; a second stimulation module used for stimulating the isolated beam nucleus; and each of the first stimulation module and the second stimulation module comprises at least two different stimulation units. Non-invasive blood pressure adjustment and control can be implemented, and the problems of low control rate and high side effect in hypertension treatment are relieved or eliminated.

The invention belongs to the field of medicines, and discloses application of ursolic acid derivatives in preparation of medicines for treating nervous system diseases. The ursolic acid is successfully subjected to structural modification by utilizing a microbial conversion technology, four novel compounds with parent nucleus structure modification are obtained, and in-vitro nerve cell injury protection tests and nerve microglia inflammation tests prove that the compounds have relatively good nerve cell protection activity and anti-neuroinflammation activity. The compound can be used as an active ingredient of medicines for treating neurodegenerative diseases, traumatic brain injury and apoplexy, and has wide application.

The invention belongs to the technical field of body temperature measurement, and particularly discloses a method for estimating body nucleus temperature from a forehead temperature and application thereof. Based on a pennes biological heat transfer model, a human forehead intracranial skull skin and soft tissue air finite element heat transfer model is established, the corresponding relation between the environment temperature and the forehead temperature is analyzed through a finite element analysis method, and meanwhile the influence of a human body temperature adjusting system on the skinand soft tissue blood flow and temperature is considered; a calculation model of the body nucleus temperature is established, and the forehead temperature can be converted into the body nucleus temperature at different environment temperatures by adopting the calculation model. The defect that a traditional forehead measuring method cannot accurately reflect the body nucleus temperature is overcome, the body nucleus temperature can be estimated through the forehead temperature in high-temperature and low-temperature environments, and the forehead measuring method has important significance incalculating the body nucleus temperature through the forehead temperature and non-contact infrared temperature measurement in epidemic prevention and control.

Techniques Nuc-seq, Div-Seq, and Dronc-Seq are allow for unbiased analysis of any complex tissue. Nuc-Seq, a scalable single nucleus RNA-Seq method, can sensitively identify closely related cell types, including within the adult hippocampus. Div-seq combines Nuc-Seq with EdU-mediated labeling of proliferating cells, allowing tracking of transcriptional dynamics of newborn neurons in an adult neurogenic region in the hippocampus. Dronc-Seq uses a microfluidic device to co-encapsulate individual nuclei in reverse emulsion aqueous droplets in an oil medium together with one uniquely barcoded mRNA-capture bead.

The invention relates to a noise deep-brain-stimulation system based on delayed feedback control. The noise deep-brain-stimulation system based on delayed feedback control is characterized by comprising two bidirectional electrodes, a microcontroller, a host computer, a noise generator and a filter, wherein the two bidirectional electrodes are separately inserted into STN in a left basal nucleus and a right basal nucleus of the brain, the bidirectional electrodes have two properties of acquisition and stimulation, acquisition of local field potentials (LFPs) of the STN of a subthalamic nucleusand application of noise stimulation are achieved, and an acquisition signal is transmitted to the microcontroller; the microcontroller comprises a pre-processing module, an estimation module and a delayed feedback control module; the host computer is used for calculating and displaying a discharge sequence, the LFPs, a discharge rate and power spectral density (PSD) of the nucleuses in the basalnucleuses, a discharge sequence and a reliability index (RI) of a thalamus nucleus and all noise parameters, and transmitting the noise parameters to the noise generator and the filter.

The invention discloses a universal multi-core brain-like processor, an accelerator card and computer equipment, the universal multi-core brain-like processor comprises a data exchange interface module and a brain-like processing unit which are connected with each other, and the brain-like processing unit comprises an on-chip network which is composed of n * n routers R and is of a C-Mesh structure, each router R is independently connected with at least one neuron nucleus used for completing neuron calculation to form a cluster, and each neuron nucleus is provided with a plurality of neuron calculation units, intra-nucleus full-connection synapses and inter-nucleus connection synapses. According to the method, simultaneous calculation and interconnection of multiple physical neurons can be supported, the future intelligent calculation development requirement can be met, a brain-like algorithm represented by a spiking neural network is executed, large-scale neuron activities are simulated, the method adapts to a continuously-developing neuromorphic calculation model, and high-energy-efficiency support and acceleration are provided for the calculation.

The invention relates to a noise depth brain stimulation system for Parkinson's disease. The noise depth brain stimulation system is characterized by consisting of a bidirectional electrode, a microcontroller, an upper computer, a noise generator and a filter, wherein the bidirectional electrode has two attributes of collection and stimulation, collection of a subthalamic nucleus (STN) nucleus local field potential (LFPs) and application of noise stimulation are respectively realized by setting the attributes of the electrode on the upper computer, and the bidirectional electrode can transmita discharge signal to a microcontroller; a Parkinson's disease state grade distribution table is stored in the upper computer, the table is divided into ten grades according to RI values, if a RI value is smaller, the Parkinson's disease state is more serious, grade classification is conducted on the current Parkinson's disease state according to the table, the parameters corresponding to noise stimulation are extracted, and the parameters are transmitted to the noise generator and the filter.