Niemeijer et al., 2009 - Google Patents

Fast detection of the optic disc and fovea in color fundus photographs

Niemeijer et al., 2009

View HTML
Document ID
3777725572675616469
Author
Niemeijer M
Abràmoff M
Van Ginneken B
Publication year
Publication venue
Medical image analysis

External Links

Snippet

A fully automated, fast method to detect the fovea and the optic disc in digital color photographs of the retina is presented. The method makes few assumptions about the location of both structures in the image. We define the problem of localizing structures in a …
Continue reading at www.ncbi.nlm.nih.gov (HTML) (other versions)

Classifications

    • 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
    • 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
    • G06T7/0014—Biomedical image inspection using an image reference approach
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • 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
    • G06T2207/30172—Centreline of tubular or elongated structure
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20092—Interactive image processing based on input by user
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20212—Image combination
    • G06T2207/20224—Image subtraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • 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
    • G06K9/00597—Acquiring or recognising eyes, e.g. iris verification
    • 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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons

Similar Documents

Publication Publication Date Title
Niemeijer et al. Fast detection of the optic disc and fovea in color fundus photographs
Bagci et al. Thickness profiles of retinal layers by optical coherence tomography image segmentation
JP4909377B2 (en) Image processing apparatus, control method therefor, and computer program
Marin et al. Obtaining optic disc center and pixel region by automatic thresholding methods on morphologically processed fundus images
Yin et al. Vessel extraction from non-fluorescein fundus images using orientation-aware detector
Niemeijer et al. Comparative study of retinal vessel segmentation methods on a new publicly available database
JP6594033B2 (en) Image processing apparatus, image processing method, and program
Tavakoli et al. A complementary method for automated detection of microaneurysms in fluorescein angiography fundus images to assess diabetic retinopathy
JP6005663B2 (en) Automatic measurement of arteriovenous ratio in blood vessel images
Köse et al. Automatic segmentation of age-related macular degeneration in retinal fundus images
Zhao et al. Saliency driven vasculature segmentation with infinite perimeter active contour model
Kolar et al. Hybrid retinal image registration using phase correlation
Gao et al. Quantification and characterisation of arteries in retinal images
JP5631339B2 (en) Image processing apparatus, image processing method, ophthalmic apparatus, ophthalmic system, and computer program
Kamble et al. Localization of optic disc and fovea in retinal images using intensity based line scanning analysis
Soares et al. Optic disc localization in retinal images based on cumulative sum fields
Pourreza-Shahri et al. Computationally efficient optic nerve head detection in retinal fundus images
Giachetti et al. The use of radial symmetry to localize retinal landmarks
Chin et al. Automatic fovea location in retinal images using anatomical priors and vessel density
Arikan et al. Deep learning based multi-modal registration for retinal imaging
Fu et al. Fovea localization by blood vessel vector in abnormal fundus images
Zaaboub et al. Optic disc detection and segmentation using saliency mask in retinal fundus images
Niemeijer et al. Automated localization of the optic disc and the fovea
Jaya Krishna et al. Retinal vessel tracking using Gaussian and radon methods
Tavakoli et al. Automated optic nerve head detection in fluorescein angiography fundus images