[go: up one dir, main page]

Taher et al., 2007 - Google Patents

Identification of lung cancer based on shape and color

Taher et al., 2007

View PDF
Document ID
13938875028014928044
Author
Taher F
Sammouda R
Publication year
Publication venue
2007 Innovations in Information Technologies (IIT)

External Links

Snippet

The analysis of sputum color images can be used to detect the lung cancer in its early stages. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid high errors. Image processing techniques provide a good tool for …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • 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
    • 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
    • G06T2207/30024Cell structures in vitro; Tissue sections in vitro
    • 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
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • 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
    • G06K9/6228Selecting the most significant subset of features
    • 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
    • G06K9/00127Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • G06K9/00147Matching; Classification
    • 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
    • G06K9/00127Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • G06K9/0014Pre-processing, e.g. image segmentation ; Feature extraction
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • 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
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • 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
    • 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
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10Investigating individual particles
    • G01N15/14Electro-optical investigation, e.g. flow cytometers
    • G01N15/1468Electro-optical investigation, e.g. flow cytometers with spatial resolution of the texture or inner structure of the particle
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications

Similar Documents

Publication Publication Date Title
Dese et al. Accurate machine-learning-based classification of leukemia from blood smear images
CN107103187B (en) Method and system for detection, grading and management of pulmonary nodules based on deep learning
Al-jaboriy et al. Acute lymphoblastic leukemia segmentation using local pixel information
CN112990214A (en) Medical image feature recognition prediction model
Xu et al. Using transfer learning on whole slide images to predict tumor mutational burden in bladder cancer patients
AU2021349226C1 (en) Critical component detection using deep learning and attention
CN113628199B (en) Pathological picture stained tissue area detection method, pathological picture stained tissue area detection system and prognosis state analysis system
US20230360208A1 (en) Training end-to-end weakly supervised networks at the specimen (supra-image) level
Taher et al. Identification of lung cancer based on shape and color
CN117576687A (en) Cervical cancer cytology screening system and method based on image analysis
Di Cataldo et al. ANAlyte: A modular image analysis tool for ANA testing with indirect immunofluorescence
Sertel et al. Computerized microscopic image analysis of follicular lymphoma
Qiu et al. Feature selection for the automated detection of metaphase chromosomes: performance comparison using a receiver operating characteristic method
Niazi et al. An automated method for counting cytotoxic T-cells from CD8 stained images of renal biopsies
Chayadevi et al. Extraction of bacterial clusters from digital microscopic images through statistical and neural network approaches
Taher et al. Morphology analysis of sputum color images for early lung cancer diagnosis
Chen et al. What can machine vision do for lymphatic histopathology image analysis: a comprehensive review
Kontoravdis et al. Cytological diagnosis based on fuzzy neural networks
Ko et al. A computer-aided grading system of breast carcinoma: scoring of tubule formation
Taher et al. Automatic sputum color image segmentation for lung cancer diagnosis
Safa'a et al. Histopathological prostate tissue glands segmentation for automated diagnosis
Taher et al. Lung Cancer Detection based on the Analysis of Sputum Color Images.
Liu et al. Deep learning-based differentiation of benign and malignant thyroid follicular neoplasms on multiscale intraoperative frozen pathological images: A multicenter diagnostic study
Fernandez et al. Analysis of Human Cervical Cell Images from Pap Smears for Classification
Kumar et al. Early Detection of Breast Cancer by Deep Learning Algorithms through Histopathological Images