1535results about How to "Improve diagnostic efficiency" patented technology

A finite element model of an ear stored on a computer readable medium having logic representing a three-dimensional geometric model of the ear; logic for meshing individual anatomical structures of the ear accounting for whether the anatomical structures include at least one of air, liquid material and solid material; logic for assigning material properties for each anatomical structure based on at least one physical property of each anatomical structure; logic for assigning boundary conditions for some of the anatomical structures indicative of interaction between such anatomical structures; and logic for employing acoustic-structural coupled analysis to the anatomical structures of the ear to generate data indicative of the acoustic effect on mechanical vibration transmission in the ear. Various embodiments of “one-chamber” and “two-chamber” analyses and models are described.

The invention relates to the fields of analysis and test, in particular to a multi-channel microfluidic chip capable of detecting various subtype swine influenza viruses (SIV) simultaneously. One of the aims of advancing the related diagnosis and treatment technology is to diagnose the SIV quickly and cheaply. The invention provides a diagnosis device, which can fulfill the aims. The key point of the scheme is that: the device, namely the microfluidic chip, comprises pipelines with a parallel structure, wherein the parallel structure comprises three branched pipelines arranged in parallel; three beads-shaped working electrodes are arranged in the three branched pipelines respectively; each beads-shaped working electrode consists of a conductive electrode and a gold colloid sensitive film; the gold colloid sensitive film is attached to the conductive electrode and embeds different subtypes of SIV specific antibodies; the gold colloid sensitive films on the surface layers of the three beads-shaped working electrodes embed three different subtypes of SIV specific antibody substances respectively; and the three different subtypes of SIV specific antibody substances are the subtype H1N1, the subtype H3N2 and the subtype H1N2 SIV specific antibody substances respectively.

The invention relates to the field of elevators. In order to early discover and diagnose A elevator fault, the invention adopts the technical scheme that an elevator fault diagnosis and early-warning method based on data drive is achieved by means of a remote service center, a fault diagnosis and prediction terminal and an elevator controller, and the method comprises the steps as follows: firstly, elevator fault data are mined to obtain characteristic information in an elevator fault data stream, and the mined result is stored in an elevator fault case base of the fault diagnosis and prediction terminal; secondly, an elevator fault knowledge base on the fault diagnosis and prediction terminal is updated by the elevator fault case base; thirdly, the case retrieval is carried out on the characteristic of a new elevator fault problem, and the fault diagnosis is carried out on the elevator system by adopting the fault diagnosis method based on the case-base reasoning; and finally information with the characteristic that is most similar with that of the new elevator fault problem is acquired through retrieval of the knowledge or the case in the elevator fault knowledge base to solve the diagnosis problem. The method is mainly suitable for manufacturing and designing image sensors.

The invention relates to a special micro-fluidic chip for cholera diagnosis with one-dimensional self-assembly magnetic bead chain electrodes, belonging to the field of testing. Rapid diagnosis of fulminating infectious disease cholera with low cost is one of many expectations in the development of medical technology, and the invention provides a micro-fluidic chip for simultaneously detecting and rapidly diagnosing cholera by using multiple characteristic antibodies of cholera. The chip is provided with three micro liquid storage tanks, and the invention is characterized in that capillary passages in parallel configuration contain in the chip, the parallel configuration contains four micro-passages that are mutually in parallel, four magnetic bead chain working electrodes are respectively installed inside the four micro-passages, the surface substances of the four magnetic bead chain working electrodes are respectively four antibody substances that are cholera TP0821 antibody, cholera TP0319 antibody, cholera TP0624 antibody and cholera O139 mycoprotein antibody. The integrated structure and the appearances of specific magnetic bead chain working electrodes facilitate to improve the diagnosis efficiency of cholera diseases.

A biological optical measuring instrument comprising a measuring probe (101) for collecting light from a plurality of portions of a subject (214) transmitted through the subject (214) by means of an optical fiber (108) by guiding light emitted from a light source (102) by an optical fiber (107), and irradiating the light to the subject (214) so as to create a living body transmitted light intensity image of the subject (214) from the transmitted and collected light. The measuring probe (101) further comprises optical fiber fixing members (201, 210, 211) for fixing the optical fibers (107, 108) at a predetermined interval and support members (202, 204, 205) for rockably supporting the optical fiber fixing members. Thus, it is possible to provide a technique of performing living body optical measurement while the living body lies in lateral decubitus.

In a medical digital X-ray imaging apparatus having a plurality of imaging modes including computed tomography mode, a supporter supports an X-ray source and a digital X-ray sensor having a two-dimensional detection plane for detecting X-rays, while interposing an object between them. An image reconstructor acquires data from the digital X-ray sensor and reconstructs an image based on the acquired data. An operator selects one of a first imaging mode and a second imaging mode. The second imaging mode has an irradiation field different from the first imaging mode and has an area to be read in the digital X-ray sensor smaller than that in the first imaging mode.

The invention relates to a fault diagnosis device and method of a fuel cell system. The fault diagnosis device comprises a communication unit, a diagnosis core unit and a man-machine interaction unit and is characterized in that the communication unit is used for receiving the procedure parameters and working condition information of a main controller as well as the single cell voltage information of a monitor unit and sending diagnosis results and various parameters and data to a field remote control monitoring center and an upper computer; the diagnosis core unit is used for detecting and positioning the faults of the sensor, actuator, controller, monitor unit and galvanic pile of the fuel cell system through the formulated diagnosis strategy; and the main-machine interaction unit is used for displaying, setting, clearing and modifying the diagnosis results and providing maintenance suggestions and measures. By considering the electrochemical reaction mechanism of fuel cells, combining the knowledge and experience of experts and adopting a multisensor information fusion method, the device can be effectively applied to the long-range, short-range, off-line and online fault diagnosis of the fuel cell system, thus the fault diagnosis accuracy and maintainability are improved.

The invention discloses a computerized auxiliary diagnosing method for malignant tumor in early stage based on deep learning algorithm. According to the invention, a deep convolution neural network is used to extract the high-level characteristics of an image layer by layer so that the obtained characteristic dimensions become smaller and smaller. To realize the dimension matching between an outputted probability predicting image and a pre-segmented image, the method uses the reverse convolution network to expand the dimensions of the characteristic image so as to obtain a dimension-consistent probability predicting image. The network generated probability predicting image extracts the binarization of the predicting image through the training of a softmax classifier to finally obtain the segmentation result of the prostate tissue. To some extent, the method effectively increases the accuracy and efficiency for doctors to diagnose prostate diseases.

A radiographic imaging apparatus includes a radiation detection circuit with elements arranged two-dimensionally to convert radiation into an electrical signal, a driving mechanism which changes a positional relationship between the components, a memory which stores that electrical signal, an imaging controller to control the radiation source so as to emit a first radiation pulse at a first energy for a first frame and to emit a second radiation pulse at a second energy for a second frame, controlling the driving mechanism to maintain the positional relationship during the first radiation pulse and the second radiation pulse and to change the positional relationship in a period between the first period and the second period. The frames are different and sequentially imaged, and an image processing unit for subtraction processing of the first and second frames in memory to generate a processed image, then generate a tomographic and a 3D image.

A dynamic layer diagnostic device for smart power grid fault comprises a data collection and monitoring unit, a data processing unit, a data base unit, a communication unit and a man-machine interaction unit. A dynamic layer diagnostic method includes: when a smart power grid breaks down, calculating fault diagnosis starting conditions to conform a diagnosis strategy, wherein the fault diagnosis strategy comprises switch layer diagnosis, feeder layer diagnosis and transformer substation layer diagnosis; starting the switch layer diagnosis when changes of switch motion information are remarkable before and after the fault; starting the transformer substation diagnosis when changes of electricity amount information are remarkable before and after the fault; stopping the diagnosis when a fault element is the only one element during the diagnosis of the switch layer; otherwise, retrieving the switch historical action recording, and starting the transformer substation diagnosis when recording matched with the current switch action exists; and otherwise, starting the feeder layer diagnosis. The dynamic layer diagnostic method performs layering analysis on the fault, fully utilizes various fault information and improves fault diagnosis accuracy according to different characteristics of multisource information after the power grid fault and difficulty layer in obtaining and processing of various information.

The invention provides a rolling bearing fault diagnosis algorithm based on time-frequency domain multidimensional fault feature fusion. Aiming at the respective features of vibration signals of a rolling bearing in a normal state, a roller fault state, an inner ring fault state and an outer ring fault state in a time-frequency domain, through extraction of time domain and frequency domain features, redundancy removal and re-fusion, fault features are described in an optimal way to obtain an intelligent judgment result. First, wavelet de-noising is performed on extracted original rolling bearing vibration data; then, time domain feature vectors are extracted to form a time domain feature matrix, and coefficient energy moments after wavelet packet decomposition and reconstruction are extracted to form a frequency domain feature matrix; and the time and frequency domain matrixes are further fused to obtain a time-frequency domain multidimensional fault feature matrix. Redundancy of the multidimensional feature matrix is eliminated to obtain a new multidimensional feature matrix. Then, information of multidimensional features is fused with a weighted feature index distance, and a state judgment result of the rolling bearing is obtained through the feature index distance obtained through fusion.

A computer readable recording medium recorded with a diagnosis supporting program, a diagnosis supporting apparatus and a diagnosis supporting method, enabling to retrieve similar disease cases making use of feature quantities of CT images and / or MRI images when interpreting such images, to thereby allow an improvement of diagnosis precision.

An electronic endoscope system has a plurality of video-processors, a plurality of video-scopes, a selector, a monitor and an input device. The plurality of video-processors, the monitor and the input device are connected to the selector. Each of the plurality of video-processors processes image signals from the corresponding video-scope to obtain and output video signals to the selector. The selector selects one of the plurality of video-processors and feeds video signals from a selected video-processor to the monitor. The input device operates the selected video-processor.

The invention provides a system for screening diabetic retinopathy. The system comprises an eyeground image obtaining device, an image processing and screening device and a report output device, wherein the eyeground image obtaining device is used for acquiring or receiving eyeground images of detected personnel; the image processing and screening device is used for processing the eyeground images and detecting whether pathology exists and then transmitting a detection result to the report output device; and the report output device outputs a corresponding detection report on the basis of the detection result. According to the system, the sensitivity of determining the diabetic retinopathy can reach 93.8%, the specificity can reach 94.5%, the precision is equivalent to manual determination precision, yet the detection time is greatly reduced, and the average detection time is 8.7 seconds, which is only one thirtieth of manual film reading time. Therefore, the scanning cost of the diabetic retinopathy can be substantially decreased, the diabetic retinopathy can be found early and treated early, the pain of patients is greatly reduced, and the clinical application prospect and the social benefits are quite good.

The invention proposes a vehicle remote diagnostic system and diagnostic method. The system includes a configured device, an in-vehicle diagnostic unit and a remote diagnostic unit. The in-vehicle diagnostic unit is connected with the remote diagnostic unit through a wireless communication network. The in-vehicle diagnostic unit includes a vehicle-mounted information entertaining system, an in-vehicle bus and the wireless communication module. The configured device is connected with the vehicle-mounted information entertaining system through the in-vehicle bus. The vehicle-mounted information entertaining system is used for receiving a diagnosis command of a user, acquiring diagnostic data and sending diagnostic data packets to the remote diagnostic unit through the wireless communication module and at the same time receiving and displaying diagnostic result data transmitted back by the wireless communication module. Through integrating a diagnostic module into the vehicle-mounted information entertaining system which is necessary for a vehicle, the vehicle remote diagnostic system and diagnostic method avoid outfitting and installation of a single diagnostic device and reduce the cost of the whole vehicle. Diagnoses can be realized through simple operations on the vehicle-mounted information entertaining system so that professional requirements for the vehicle diagnoses are reduced and at the same time, remote-diagnosis performance and efficiency are improved greatly at the same time.

The invention discloses an intelligent medical information remote processing system and an intelligent medical information remote processing method, and belongs to the technical field of medical diagnosis. The system comprises a remote processing end and remotely connected client ends, wherein the remote processing end comprises a communication unit, a first receiving unit, a first sending unit, a classifying unit, a storage unit and a sub-processing unit; the intelligent medical information remote processing method comprises the following steps that medical information sent by the client ends is acquired and sent to the corresponding sub-processing unit; disease condition information in the medical information and default medical information are matched by the sub-processing unit to obtain corresponding diagnostic information and / or treatment information; the remote processing end sends a processing result of the sub-processing unit to the client ends; the sub-processing unit updates the default medical information in the remote processing end according to the diagnostic information and / or the treatment information in the medical information. The technical scheme of the invention has the benefits of optimizing a whole treatment process to effectively improve the diagnostic accuracy and diagnostic efficiency of a doctor, and facilitating systemic storage of the medical information.

The invention discloses an electronic medical record database system which comprises a data entry module, a user login module, a data storage module, a data management module and a query analysis module, wherein the data entry module is used for entering electronic medical record data; the user login module is used for a user to log in the electronic medical record database system, and carrying out identity authentication and authority identification; the data storage module is used for storing the electronic medical record data and the individual information and authority information of the user; the data management module is used for setting and managing the individual information and the authority information of the user, and adding, deleting and modifying data in the data storage module according to input orders of the user with authority based on the authentication and identification results of the user login module; and the query analysis module is used for querying the electronic medical record data according to the query criteria input by the user, and counting and analyzing the query results to obtain the analyzed medical record data. The invention establishes the electronic medical records of patients, standardizes data management of the patients, and provides an approach to analysis and diagnosis for medical care personnel.

The invention provides a method for diagnosing a fault by a functional fault directed graph, which can be applied to the field of fault diagnosis for some systems of aircrafts (such as an air source system, an anti-icing system and an air-conditioning system of an airplane gas path). The method comprises the steps of: decomposing a diagnosis object system to determine component relation and build a system structural model, confirming the corresponding input and output based on the component functions, determining the component fault model, analyzing fault propagation path and influence relation, setting test points and test information of a sensor, monitoring parameter variation that indicates the potential fault, forming an FF-SDG model, and at last, searching the potential fault source by a hierarchical policy inference method based on the FF-SDG model to perform fault diagnosis. The method can quickly and effectively find out the system fault source of the aircraft system, discover the fault cause, and make up shortage of the fault diagnosis technique based on manuals and cases when some fault cannot be predicated and the knowledge is difficult to be acquired by domain experts.

The present invention provides a method, device, equipment for the segmentation of a lesion in a biological image and a storage medium. The method comprises a step of acquiring a target biological image, a step of performing coarse segmentation processing on the target biological image and obtaining a coarse segmentation mask after the rough segmentation processing, wherein the coarse segmentationmask includes information of candidate lesions in the target biological image, a step of identifying a non-real lesion from the candidate lesions, correcting the rough segmentation mask based on a recognition result such that the information of an identified non-real lesion is not included in the coarse segmentation mask and a target segmentation mask obtained after the correction is used as a lesion segmentation mask corresponding to the target biological image. According to the method, the device, the equipment and the storage medium, the lesion can be automatically positioned from the target biological image, the mode is labor-saving, the time consumption of the positioning of the lesion is reduced, misdiagnosis and missed diagnosis caused by the manual positioning of the lesion are avoided, the positioned lesion can also assist the doctor to carry out fast and accurate analysis, and the diagnostic efficiency and diagnostic accuracy of doctors are improved.

The invention relates to the field of molecular biology and aims to provide an ARMS-qPCR (Allele Refractory Mutation System-quantitative Polymerase Chain Reaction) detection kit for KRAS (Kirsten Rat Sarcoma Viral Oncogene Homolog) gene mutation subtype and a detection method. The kit comprises a qPCR hybrid reaction solution, a locked nucleic acid retardant probe, a reference primer, an ARMS primer and a positive control sample, wherein the qPCR hybrid reaction solution comprises a PCR buffer solution, dNTPs (Deoxynucleotide Triphosphates), MgCl2, GoldStarbest Taq enzyme, a universal PCR reverse primer and a universal TaqMan probe. The kit provided by the invention can be used for rapidly and accurately detecting specific locus mutation of KRAS genes in various cancer tissues with high sensitivity, has high sensitivity, and can be used for detecting genome DNA with various tissue origins, specially free DNA segments adopting cell-free systems, such as blood serum and blood plasma, orother body fluid origins, wherein the genome DNA is derived from cell systems. Compared with direct sequencing and other mutation detection technologies, the kit and the detection method thereof havethe advantages of strong specificity, high sensitivity, simplicity and rapidness in operation, high throughput, safety, definiteness and objectivity in result identification and the like for detecting the KRAS gene mutation.

An ultrasonic diagnostic apparatus (ultrasonic elastograph) for measuring strain or elastic modulus of a tissue or an organ of a living body, creating a strain image or an elastic modulus image by assigning a hue to the measurement data corresponding to the measured value, combining these images with a black and white tomogram, displaying the synthetic image on a color monitor, and displaying the hue assigned to the measurement data with a color bar. Information on comparison between a measured value corresponding to the hue of the color bar displayed on the color monitor and the reference value of the measured value is displayed at a position adjacent to the color bar on the screen of the color monitor.

Bearing fault diagnosis based on pseudo-tag semi-supervised kernel local Fisher discriminant analysis is provided. The method is characterized in comprising the following steps: (1) collecting vibration signals of bearings under different working conditions to form a training sample; (2) performing feature extraction on the training sample obtained in (1); (3) performing normalization processing on features obtained in (2); (4) obtaining a clustering tag set by using density peak clustering for the entire feature set obtained in (3); (5) using clustering pseudo-tags obtained in (4) to construct local inter-cluster divergence and intra-cluster divergence regularization terms, and combining the regularization terms with the inter-class divergence and intra-class divergence with tag samples in the FDA to determine a final projection vector; (6) using the final projection vector obtained in (5) to solve a projection set of the tagged feature set in the dimensionality reduction space; (7) using the projection set obtained in (6) to train an extreme learning machine; and (8) performing processing of (2), (3) and (5) on the collected vibration signals, and inputting the processed vibration signals to determine the working conditions. The technical scheme of the present invention is applied to the problem of fault identification of bearing equipment.

The invention relates to a three dimensional matching method for lung CT. The three dimensional matching method comprises steps that: first lung CT body data and second lung CT body data are loaded, mutual information is taken as matching measure, three dimensional rigid matching for the first lung CT body data and the second lung CT body data is carried out to make lung portion areas of the two are aligned integrally, displacement parameters and rotating parameters in three directions of X, Y and Z axes are recorded and are taken as first matching parameters; on the basis of rigid matching, non-rigid matching is carried out, the optimal displacement field of the non-rigid matching is recorded and is taken as the second matching parameter; the first matching parameters and the second matching parameter are utilized to carry out matching of nodules in the first lung CT body data and the second lung CT body data to establish corresponding relations. The three dimensional matching method can realize accurate matching, a nodule focus at the same position is enabled to automatically correspond to imaging positions in different CT data by utilizing the matching result, and thereby the method is convenient for a doctor to contrast nodule disease development conditions.

The invention provides a method for locating and identifying a lesion of a medical image, a device, an equipment and a storage medium. The method comprises the following steps of obtaining a target image, wherein the target image is a medical image to be localized and identified; preprocessing the target image to obtain a preprocessed image; inputting the pre-processed images into the pre-established lesion location recognition model, and obtaining the corresponding lesion location indication map of the target image and the lesion classification in the target image; obtaining the lesion location recognition model by training medical images with the lesion classification labeled; The lesion location recognition model based on that present application can automatically detect a lesion from amedical image, the location of the lesion is given, which not only saves manpower and reduces the time consumed in identifying and locating the lesion, but also avoids the misdiagnosis, missed diagnosis, locating and identifying lesion caused by manual locating and locating the lesion, which can also assist doctors to carry out rapid and accurate analysis, and improves the diagnosis efficiency and accuracy of doctors.

An X-ray tube generates X-rays. An X-ray detector detects X-rays generated from the X-ray tube and transmitted through an object to be examined. A rotating frame continuously rotates the X-ray tube and the X-ray detector around the object. A reconstruction unit reconstructs a plurality of first volume data sets with different scan times for the same scan area of the object on the basis of an output from the X-ray detector. An image processing unit generates single second volume data set corresponding to a maximum value, an average value, a median value, or minimum value of the plurality of reconstructed first volume data sets in the temporal direction.

The invention discloses a fault diagnosis and prediction method for a numerical control machine tool spindle, and belongs to the field of numerical control machine tools. The method includes the following steps of database establishment, signal acquisition and analysis, fault diagnosis and fault prediction. Advanced artificial intelligence technologies such as a nerve network, an expert system and a support vector machine are used for conducting fault diagnosis and prediction, measured data transmitted from a high-precision laser displacement sensor, an infrared temperature sensor and an acceleration sensor are rapidly analyzed through a mixed reasoning model, fault sources are effectively inferred and fault diagnosis and prediction of the numerical control machine tool spindle are conducted in the running process of the numerical control machine tool spindle according to numerical control machine tool spindle models established by various machine tools, and therefore the fault diagnosis accuracy and efficiency of the numerical control machine tool spindle are greatly improved, relative prediction is conducted on the tendency of the state of the numerical control machine tool spindle, and the maintenance cost of the numerical control machine tool spindle is effectively reduced.

A computer readable recording medium recorded with a diagnosis supporting program, a diagnosis supporting apparatus and a diagnosis supporting method, enabling to retrieve similar disease cases making use of feature quantities of CT images and / or MRI images when interpreting such images, to thereby allow an improvement of diagnosis precision.

A medical image diagnosis support device comprises an organ region setting means, a deformation degree calculating means for calculating the deformation degree of the organ region set by the organ region setting means, a reference value storing means, a lesion detecting means for comparing the stored reference value with the deformation degree calculated by the deformation calculating means and for detecting existence of a lesion of the organ region from the comparison result, and a presenting means for presenting the existence to the examiner at least either visually or auditorily. Thus, the device can make a diagnosis selectively only on an organ region deformed because of a lesion and present it to the examiner visually such as by means of an image display or auditorily such as by means of speech, thereby improving the efficiency of diagnosis.

The invention discloses an optical coherent tomographic image retinopathy intelligent testing system and a testing method. A current acquired retina image is mainly determined by an ophthalmology doctor by means of naked eye observation, and large-scale popularization is not facilitated. According to the system, a deep learning concept is used as a technical core; a migration learning strategy isutilized; a convolutional neural network algorithm in a deep learning model is used for establishing a classifier, thereby realizing classification of retinopathy; furthermore an image segmenting algorithm is used for realizing focus extraction and retina layering, thereby obtaining specific information of a pathology position in a picture and quantification information of shape parameters, and generating a related diagnosis report for further diagnosis by the doctor. The optical coherent tomographic image retinopathy intelligent testing system and the testing method have advantages of fillingin gaps in pathology intelligent identification and accurate positioning in a current optical coherent chromatography imaging system, effectively reducing working intensity of the doctor, and furtherpromoting clinical application and technical development of the optical coherent chromatography imaging system in ophthalmology disease diagnosis.