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

Krishnamoorthi et al., 2019 - Google Patents

Hybrid feature vector based detection of Glaucoma

Krishnamoorthi et al., 2019

Document ID
13267496906854711054
Author
Krishnamoorthi N
Chinnababu V
Publication year
Publication venue
Multimedia Tools and Applications

External Links

Snippet

This paper focus on the investigation of the potential in retinal image analysis for the detection of Glaucoma. The computer-based analysis of the parameter involves the use of image processing algorithms for pre-processing, localization and segmentation of the region …
Continue reading at link.springer.com (other versions)

Classifications

    • 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
    • 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
    • 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
    • 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
    • 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
    • G06T2207/10072Tomographic images
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color image
    • 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
    • G06K9/00221Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268Feature extraction; Face representation
    • G06K9/00281Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • 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
    • G06K2209/051Recognition of patterns in medical or anatomical images of internal organs
    • 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

Similar Documents

Publication Publication Date Title
Mo et al. Exudate-based diabetic macular edema recognition in retinal images using cascaded deep residual networks
Chowdhury et al. A Random Forest classifier-based approach in the detection of abnormalities in the retina
Thakur et al. Optic disc and optic cup segmentation from retinal images using hybrid approach
Salam et al. Automated detection of glaucoma using structural and non structural features
Akram et al. Automated detection of exudates and macula for grading of diabetic macular edema
Kausu et al. Combination of clinical and multiresolution features for glaucoma detection and its classification using fundus images
Akram et al. Identification and classification of microaneurysms for early detection of diabetic retinopathy
Akram et al. Detection of neovascularization in retinal images using multivariate m-Mediods based classifier
Hosseini et al. Review of medical image classification using the adaptive neuro-fuzzy inference system
Akbar et al. Automated techniques for blood vessels segmentation through fundus retinal images: A review
Melo et al. Microaneurysm detection in color eye fundus images for diabetic retinopathy screening
Panda et al. New binary Hausdorff symmetry measure based seeded region growing for retinal vessel segmentation
Mahbod et al. Automatic brain segmentation using artificial neural networks with shape context
Abdelhafeez et al. Skin cancer detection using neutrosophic c-means and fuzzy c-means clustering algorithms
Zulfira et al. Segmentation technique and dynamic ensemble selection to enhance glaucoma severity detection
Sakthivel et al. An automated detection of glaucoma using histogram features
Cervantes et al. A comprehensive survey on segmentation techniques for retinal vessel segmentation
Panda et al. Glauconet: patch-based residual deep learning network for optic disc and cup segmentation towards glaucoma assessment
Krishnamoorthi et al. Hybrid feature vector based detection of Glaucoma
Karkuzhali et al. Robust intensity variation and inverse surface adaptive thresholding techniques for detection of optic disc and exudates in retinal fundus images
Chen et al. Combination of enhanced depth imaging optical coherence tomography and fundus images for glaucoma screening
Li et al. An unsupervised retinal vessel extraction and segmentation method based on a tube marked point process model
Singh et al. A review on retinal vessel segmentation and classification methods
Bu et al. Hierarchical Detection of Hard Exudates in Color Retinal Images.
Ullaha et al. Optic disc segmentation and classification in color fundus images: a resource-aware healthcare service in smart cities