Nothing Special   »   [go: up one dir, main page]

Moosavi et al., 2024 - Google Patents

Segmentation and classification of lungs CT-scan for detecting COVID-19 abnormalities by deep learning technique: U-Net model

Moosavi et al., 2024

View HTML
Document ID
16831664027155453236
Author
Moosavi A
Mahboobi A
Arabzadeh F
Ramezani N
Moosavi H
Mehrpoor G
Publication year
Publication venue
Journal of Family Medicine and Primary Care

External Links

Snippet

Background: Artificial intelligence (AI) techniques have been ascertained useful in the analysis and description of infectious areas in radiological images promptly. Our aim in this study was to design a web-based application for detecting and labeling infected tissues on …
Continue reading at journals.lww.com (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345—Medical expert systems, neural networks or other automated diagnosis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G06F19/321—Management of medical image data, e.g. communication or archiving systems such as picture archiving and communication systems [PACS] or related medical protocols such as digital imaging and communications in medicine protocol [DICOM]; Editing of medical image data, e.g. adding diagnosis information
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G06F19/322—Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Health care, e.g. hospitals; Social work
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Christe et al. Computer-aided diagnosis of pulmonary fibrosis using deep learning and CT images
Al-Antari et al. Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images
Wang et al. A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis
Pham A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks
Chang et al. Hybrid 3D/2D convolutional neural network for hemorrhage evaluation on head CT
Gonzalez et al. Disease staging and prognosis in smokers using deep learning in chest computed tomography
Ong et al. Machine learning and natural language processing methods to identify ischemic stroke, acuity and location from radiology reports
Cicero et al. Training and validating a deep convolutional neural network for computer-aided detection and classification of abnormalities on frontal chest radiographs
Khan et al. A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron
He et al. Benchmarking deep learning models and automated model design for COVID-19 detection with chest CT scans
Abdulkareem et al. [Retracted] Automated System for Identifying COVID‐19 Infections in Computed Tomography Images Using Deep Learning Models
Barbosa Jr et al. Automated detection and quantification of COVID-19 airspace disease on chest radiographs: a novel approach achieving expert radiologist-level performance using a deep convolutional neural network trained on digital reconstructed radiographs from computed tomography-derived ground truth
Dack et al. Artificial intelligence and interstitial lung disease: Diagnosis and prognosis
Suman et al. Attention based CNN-LSTM network for pulmonary embolism prediction on chest computed tomography pulmonary angiograms
Khan et al. COVID-19 infection analysis framework using novel boosted CNNs and radiological images
Kaba et al. The application of deep learning for the segmentation and classification of coronary arteries
Guo et al. Deep learning with weak annotation from diagnosis reports for detection of multiple head disorders: a prospective, multicentre study
Aktas et al. Deep convolutional neural networks for detection of abnormalities in chest X-rays trained on the very large dataset
Olescki et al. A two step workflow for pulmonary embolism detection using deep learning and feature extraction
Ghosh et al. A quantitative lung computed tomography image feature for multi-center severity assessment of COVID-19
US20220285011A1 (en) Document creation support apparatus, document creation support method, and program
JP2024528381A (en) Method and system for automatically tracking and interpreting medical image data
Moosavi et al. Segmentation and classification of lungs CT-scan for detecting COVID-19 abnormalities by deep learning technique: U-Net model
Chaya et al. Predictive analysis by ensemble classifier with machine learning models
Yenurkar et al. Effective detection of COVID-19 outbreak in chest X-Rays using fusionnet model