Lau et al., 2014 - Google Patents
The singapore eye vessel assessment systemLau et al., 2014
- Document ID
- 3394848144524871032
- Author
- Lau Q
- Lee M
- Hsu W
- Wong T
- Ng E
- Acharya U
- Campillo A
- Suri J
- Publication year
- Publication venue
- Image analysis and modeling in ophthalmology
External Links
Snippet
Images of the retina provide one of the few avenues to observe human microcirculation in a noninvasive manner. A variety of measurements have been proposed over the years1 to quantify multiple aspects of retinal vascular morphology. Many of these measures have …
- 238000005259 measurement 0 abstract description 44
Classifications
-
- 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
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
-
- 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
- G06T2207/20112—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
- G06T2207/10024—Color image
-
- 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
- G06T2207/20101—Interactive definition of point of interest, landmark or seed
-
- 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
- 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
- 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
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00268—Feature extraction; Face representation
- G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- 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
- G06K2209/05—Recognition of patterns in medical or anatomical images
- G06K2209/051—Recognition of patterns in medical or anatomical images of internal organs
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Martinez-Perez et al. | Retinal vascular tree morphology: a semi-automatic quantification | |
Estrada et al. | Retinal artery-vein classification via topology estimation | |
AU2014289978B2 (en) | Quantifying a blood vessel reflection parameter of the retina | |
EP2262410B1 (en) | Retinal image analysis systems and method | |
Fraz et al. | QUARTZ: Quantitative Analysis of Retinal Vessel Topology and size–An automated system for quantification of retinal vessels morphology | |
Lau et al. | Simultaneously identifying all true vessels from segmented retinal images | |
Vázquez et al. | Improving retinal artery and vein classification by means of a minimal path approach | |
Huang et al. | Retinal artery/vein classification using genetic-search feature selection | |
Leontidis et al. | A new unified framework for the early detection of the progression to diabetic retinopathy from fundus images | |
Aquino | Establishing the macular grading grid by means of fovea centre detection using anatomical-based and visual-based features | |
Kang et al. | AVNet: A retinal artery/vein classification network with category-attention weighted fusion | |
Nisha et al. | A computer-aided diagnosis system for plus disease in retinopathy of prematurity with structure adaptive segmentation and vessel based features | |
Lau et al. | The singapore eye vessel assessment system | |
EP4045138A1 (en) | Systems and methods for monitoring the functionality of a blood vessel | |
CN111797900A (en) | Arteriovenous classification method and device of OCT-A image | |
Morales et al. | Segmentation and analysis of retinal vascular tree from fundus images processing | |
US20220061920A1 (en) | Systems and methods for measuring the apposition and coverage status of coronary stents | |
Poletti et al. | Automatic nerve tracking in confocal images of corneal subbasal epithelium | |
Lyu et al. | Construction of retinal vascular trees via curvature orientation prior | |
Zhou et al. | Computer aided diagnosis for diabetic retinopathy based on fundus image | |
Vázquez et al. | Automatic arteriovenous ratio computation: Emulating the experts | |
Oloumi et al. | Computer-aided diagnosis of retinopathy of prematurity in retinal fundus images | |
Lin et al. | Vascular tree construction with anatomical realism for retinal images | |
CN117876801B (en) | Method for predicting diabetic nephropathy based on fundus blood vessel characteristics and artificial intelligence | |
Lin et al. | Retinal vascular tree construction with multimodal fluorescein angiogram sequence |