[go: up one dir, main page]

Kumar et al., 2024 - Google Patents

A methodical exploration of imaging modalities from dataset to detection through machine learning paradigms in prominent lung disease diagnosis: a review

Kumar et al., 2024

View HTML @Full View
Document ID
8406965984103175497
Author
Kumar S
Kumar H
Kumar G
Singh S
Bijalwan A
Diwakar M
Publication year
Publication venue
BMC Medical Imaging

External Links

Snippet

Background Lung diseases, both infectious and non-infectious, are the most prevalent cause of mortality overall in the world. Medical research has identified pneumonia, lung cancer, and Corona Virus Disease 2019 (COVID-19) as prominent lung diseases prioritized …
Continue reading at link.springer.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
    • 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
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • 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
    • G06K9/6279—Classification techniques relating to the number of classes
    • 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
    • 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
    • G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
    • 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
    • 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
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • 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
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • 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

Similar Documents

Publication Publication Date Title
Kumar et al. A methodical exploration of imaging modalities from dataset to detection through machine learning paradigms in prominent lung disease diagnosis: a review
Alghamdi et al. Deep learning approaches for detecting COVID-19 from chest X-ray images: A survey
Shamrat et al. High-precision multiclass classification of lung disease through customized MobileNetV2 from chest X-ray images
Wang et al. Prior-attention residual learning for more discriminative COVID-19 screening in CT images
Al-qaness et al. Chest X-ray images for lung disease detection using deep learning techniques: a comprehensive survey
Xie et al. Computer‐Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs
Ibrahim et al. Effective hybrid deep learning model for COVID‐19 patterns identification using CT images
Causey et al. Spatial pyramid pooling with 3D convolution improves lung cancer detection
Yi et al. Multi-label softmax networks for pulmonary nodule classification using unbalanced and dependent categories
Sreenivasu et al. [Retracted] Dense Convolutional Neural Network for Detection of Cancer from CT Images
Akbarnezhadsany et al. YOLOv8 outperforms traditional CNN models in mammography classification: insights from a multi‐institutional dataset
Xu et al. Pulmonary textures classification via a multi-scale attention network
Naik et al. Prediction of malignancy in lung nodules using combination of deep, fractal, and gray-level co-occurrence matrix features
Isaac et al. Computer-aided diagnosis system for diagnosis of cavitary and miliary tuberculosis using improved artificial bee colony optimization
Xu et al. Identification of benign and malignant lung nodules in CT images based on ensemble learning method
Kalkeseetharaman et al. A bird’s eye view approach on the usage of deep learning methods in lung cancer detection and future directions using x-ray and ct images
Lu et al. CvTGNet: A Novel Framework for Chest X-Ray Multi-label Classification
Ennaji et al. Ensemble learning with weighted voting classifier for melanoma diagnosis
Kordnoori et al. Advances in medical image analysis: A comprehensive survey of lung infection detection
Zhu et al. Cross-ViT based benign and malignant classification of pulmonary nodules
Geroski et al. Enhancing COVID-19 disease severity classification through advanced transfer learning techniques and optimal weight initialization schemes
Zhuang et al. An interpretable multi-task system for clinically applicable COVID-19 diagnosis using CXR
Abdullah et al. Enhanced feature selection algorithm for pneumonia detection
Alhassan Thresholding Chaotic Butterfly Optimization Algorithm with Gaussian Kernel (TCBOGK) based segmentation and DeTrac deep convolutional neural network for COVID-19 X-ray images
Aitimov et al. Classification of pathologies on digital chest radiographs using machine learning methods