[go: up one dir, main page]

Bharathi et al., 2022 - Google Patents

Neural Network based Earlier Stage Lung Cancer Prediction Scheme with Differential Learning Assistance

Bharathi et al., 2022

Document ID
5578707136033072673
Author
Bharathi P
et al.
Publication year
Publication venue
2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)

External Links

Snippet

Cancer estimate and prediction are a difficult problem to examine and correct in the image processing arena. In comparison to tumor predictions, cancer initial estimates seem to be more complicated due to the fact that they are entirely cell-based perspectives that are …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-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
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • G06T7/0014Biomedical image inspection using an image reference approach
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K2209/05Recognition of patterns in medical or anatomical images
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA 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
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/22Health care, e.g. hospitals; Social work

Similar Documents

Publication Publication Date Title
Masood et al. Computer-assisted decision support system in pulmonary cancer detection and stage classification on CT images
US12039724B2 (en) Methods of assessing lung disease in chest x-rays
CN112292691A (en) Methods and systems for improving cancer detection using deep learning
CN109948667A (en) Image classification method and device for prediction of distant metastasis of head and neck cancer
Reddy et al. Intelligent deep learning algorithm for lung cancer detection and classification
Cifci SegChaNet: a novel model for lung cancer segmentation in CT scans
Fatima et al. Analyzing breast cancer detection using machine learning & deep learning techniques
Yar et al. Lung nodule detection and classification using 2D and 3D convolution neural networks (CNNs)
Paliwal et al. A comprehensive analysis of identifying lung cancer via different machine learning approach
Siddiqui et al. Computed tomography image Processing methods for lung nodule detection and classification: a review
Sasikumar et al. Deep convolutional generative adversarial networks for automated segmentation and detection of lung adenocarcinoma using red deer optimization algorithm
Moon et al. Transformer based on the prediction of psoriasis severity treatment response
Costa et al. A deep learning-based radiomics approach for covid-19 detection from cxr images using ensemble learning model
Khouadja et al. Lung Cancer Detection with Machine Learning and Deep Learning: A Narrative Review
Ewaidat et al. Identification of lung nodules CT scan using YOLOv5 based on convolution neural network
Seetha et al. The Smart Detection and Analysis on Skin Tumor Disease Using Bio Imaging Deep Learning Algorithm
Manikandan et al. Hybrid computational intelligence for healthcare and disease diagnosis
Abolghasemi et al. Accuracy improvement of breast tumor detection based on dimension reduction in the spatial and edge features and edge structure in the image
Bharathi Neural Network based Earlier Stage Lung Cancer Prediction Scheme with Differential Learning Assistance
CN116825291A (en) Deep learning model establishment method for accurately diagnosing lung adenocarcinoma air cavity internal dispersion
Wang et al. Identification of lesion bioactivity in hepatic cystic echinococcosis using a transformer-based fusion model
Wahengbam et al. Deep learning-based early lung cancer detection using multi-model image fusion technique
Sajiv et al. Machine Learning based Analysis of Histopathological Images of Breast Cancer Classification using Decision Tree Classifier
SureshKumar et al. Integrated global and local feature extraction and classification from computerized tomography (CT) images for lung cancer classification
Taheri et al. GoogleNet’s semantic hierarchical feature fusion for the classification of lung cancer CT images