Patents
Literature
Hiro is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Hiro

45 results about "Benign lesion" patented technology

A benign lesion is non-cancerous whereas a malignant lesion is cancerous. For example, a biopsy of a skin lesion may prove it to be benign or malignant, or evolving into a malignant lesion (called a premalignant lesion). Lesions can be defined according to the patterns they form.

Tumor malignant risk stratification auxiliary diagnosis system of artificial intelligence medical image

ActiveCN109166105AIncreased diagnostic confidenceReduce anxietyImage enhancementImage analysisLower riskData acquisition
The invention discloses a tumor malignant risk stratification auxiliary diagnosis system of an artificial intelligence medical image. The system comprises a data acquisition module, a data preprocessing module, a model establishment module, a model verification and optimization module, a stratification diagnosis module and a database platform. The tumor malignant risk stratification auxiliary diagnosis system of the invention is based on artificial intelligence technology, successive stratification of the malignant risk of the tumor can be achieved, the clinical diagnosis thinking is simulated, based on the high-precision ability of detecting benign lesions and malignant tumors of artificial intelligence model, and the space-occupying lesions with definite imaging features are diagnosed automatically. As a result, the system can substantially assist the clinical management decision of space-occupying lesions, improve the existing work flow of clinical diagnosis, increase the confidenceof doctors in diagnosis, reduce the work pressure, reduce the anxiety of patients with low-risk malignant lesions, greatly improve the diagnostic rate of benign lesions and malignant tumors, and hopefully realize the landing implementation of artificial intelligence clinical auxiliary diagnosis.
Owner:NANJING GENERAL HOSPITAL NANJING MILLITARY COMMAND P L A

Breast ultrasonic image multi-classification system and method based on cross correlation characteristics

ActiveCN107358267AImprove auxiliary diagnosis effectMeet needsImage enhancementImage analysisFeature vectorSonification
The invention provides a breast ultrasonic image multi-classification system and method based on cross correlation characteristics. The system comprises an ultrasonic image preprocessing unit; an interest area extraction unit used for extracting an image of an interest area; an internal cross correlation density feature extraction unit used for extracting an internal cross correlation density characteristic value of an interest image; a conventional feature extraction unit used for extracting a plurality of conventional characteristic values of the interest area image; and a multi-classification unit used for training classifiers, inputting an internal cross correlation density characteristic value vector and conventional characteristic vectors to three trained classifiers for classification, and regarding the category with the most prediction as a final classification result. According to the classification method, the internal cross correlation density characteristic based on the interest area is additionally provided, the auxiliary diagnosis effect of a breast ultrasonic computer can be effectively improved, the classification category of galactocele which is the benign lesion is added, and the requirement of a breast ultrasonic computer auxiliary system by doctors is further met.
Owner:NORTHEASTERN UNIV

Machine learning-based bimodal image omics ground glass nodule classification method

The invention belongs to the technical field of medical treatment, and discloses a machine learning-based bimodal image omics ground glass nodule classification method, which comprises the following steps of: step 1, case data collection: collecting patients who receive 18F-FDG PET/CT examination due to suspicious ground glass nodules (GGN); step 2, image acquisition and reconstruction: performing image acquisition by adopting a PET/CT (positron emission tomography/computed tomography) imaging instrument; step 3, image feature extraction; and step 4, data processing and analysis. According to the method, the image omics model based on the combination of the PET image and the HRCT image is constructed by applying a machine learning method, the GGN is classified, including pre-infiltration lesion, micro-infiltration adenocarcinoma, infiltration adenocarcinoma and benign lesion, verification and testing, the method is good in robustness, high in accuracy, simple and feasible. According to the method, the functional metabolism information and the physical anatomical information of the molecular level of the focus are integrated, the prediction efficiency of traditional CT parameters and single CT radiomics is effectively improved, and clinical management of the GGN is facilitated.
Owner:THE FIRST PEOPLES HOSPITAL OF CHANGZHOU

Apparatus for treating breast lesions using microwaves

A method for selectively heating cancerous conditions of the breast including invasive ductal carcinoma and invasive glandular lobular carcinoma, and pre-cancerous conditions of the breast including ductal carcinoma in-situ, lobular carcinoma in-situ, and intraductal hyperplasia, as well as benign lesions (any localized pathological change in the breast tissue) such as fibroadenomas and cysts by irradiation of the breast tissue with adaptive phased array focused microwave energy is introduced. Microwave energy provides preferential heating of high-water content breast tissues such as carcinomas, fibroadenomas, and cysts compared to the surrounding lower-water content normal breast tissues. To focus the microwave energy in the breast, the patient's breast can be compressed and a single electric-field probe, inserted in the central portion of the breast, or two noninvasive electric-field probes on opposite sides of the breast skin, can be used to measure a feedback signal to adjust the microwave phase delivered to waveguide applicators on opposite sides of the compressed breast tissue. The initial microwave power delivered to the microwave applicators is set to a desired value that is known to produce a desired increase in temperature in breast tumors. Temperature feedback sensors are used to measure skin temperatures during treatment to adjust the microwave power delivered to the waveguide applicators to avoid overheating the skin. The microwave energy delivered to the waveguide applicators is monitored in real time during treatment, and the treatment is completed when a desired total microwave energy dose has been administered. By heating and destroying the breast lesion sufficiently, lesions can be reduced in size and surrounding normal breast tissues are spared so that surgical mastectomy can be replaced with surgical lumpectomy or the lesions can be completely destroyed so that surgical mastectomy or lumpectomy is avoided.
Owner:CELSION CANADA

A system and method for multiple classification of breast ultrasound images based on cross-correlation features

ActiveCN107358267BImprove auxiliary diagnosis effectMeet needsImage enhancementImage analysisMultivariate classificationBreast ultrasonography
The invention provides a system and method for multiple classification of breast ultrasound images based on cross-correlation features, including an ultrasound image preprocessing unit; a region of interest extraction unit for extracting images of the region of interest; an internal cross-correlation density feature extraction unit for extracting sense The internal cross-correlation density eigenvalue of the image of interest; the traditional feature extraction unit is used to extract a variety of traditional eigenvalues ​​of the image of the region of interest; the multi-class classification unit is used to train the classifier and convert the internal cross-correlation density eigenvalue vector The traditional feature vectors are input to the three trained classifiers for classification, and the most predicted category is taken as the final classification result. The classification method of the present invention increases the feature based on the internal cross-correlation density of the region of interest, can effectively improve the effect of breast ultrasound computer-aided diagnosis, and increases the classification category of breast cysts, a benign lesion, and further satisfies doctors' requirements for breast ultrasound computer-aided systems. demand.
Owner:NORTHEASTERN UNIV LIAONING

Tumor malignancy risk stratification auxiliary diagnosis system based on artificial intelligence medical imaging

ActiveCN109166105BIncreased diagnostic confidenceReduce anxietyImage enhancementImage analysisAlgorithmData acquisition
The invention discloses an artificial intelligence medical imaging system for auxiliary diagnosis of tumor malignant risk stratification, comprising: a data acquisition module, a data preprocessing module, a model establishment module, a model verification and optimization module, a hierarchical diagnosis module and a database platform. The auxiliary diagnosis system for tumor malignant risk stratification of the present invention is based on artificial intelligence technology, which can realize successive stratification of malignant risk of tumors, simulate clinical diagnosis ideas, and detect benign lesions and malignant tumors with high precision using artificial intelligence models The ability to automatically diagnose space-occupying lesions with clear imaging features can substantially assist clinical management decision-making of space-occupying lesions, improve the existing workflow of clinical diagnosis, increase physicians' confidence in diagnosis, reduce work pressure, and reduce the risk of low malignancy The anxiety of patients with lesions has greatly improved the diagnosis rate of benign lesions and malignant tumors, and it is expected to realize the implementation of artificial intelligence clinical auxiliary diagnosis.
Owner:NANJING GENERAL HOSPITAL NANJING MILLITARY COMMAND P L A
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products