Soomro et al., 2017 - Google Patents
Computerised approaches for the detection of diabetic retinopathy using retinal fundus images: a surveySoomro et al., 2017
View PDF- Document ID
- 17656455424629770335
- Author
- Soomro T
- Gao J
- Khan T
- Hani A
- Khan M
- Paul M
- Publication year
- Publication venue
- Pattern Analysis and Applications
External Links
Snippet
Eye-related disease such as diabetic retinopathy (DR) is a medical ailment in which the retina of the human eye is smashed because of damage to the tiny retinal blood vessels in the retina. Ophthalmologists identify DR based on various features such as the blood …
- 238000001514 detection method 0 title abstract description 154
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
- G06T2207/30041—Eye; Retina; Ophthalmic
-
- 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
-
- 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
- G06T2207/10101—Optical tomography; Optical coherence tomography [OCT]
-
- 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
- G06T2207/10088—Magnetic resonance imaging [MRI]
-
- 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
- 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
- G06T2207/20112—Image segmentation details
-
- 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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
-
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
-
- 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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Soomro et al. | Computerised approaches for the detection of diabetic retinopathy using retinal fundus images: a survey | |
Winder et al. | Algorithms for digital image processing in diabetic retinopathy | |
Fraz et al. | Blood vessel segmentation methodologies in retinal images–a survey | |
Annunziata et al. | Leveraging multiscale hessian-based enhancement with a novel exudate inpainting technique for retinal vessel segmentation | |
Mookiah et al. | Computer-aided diagnosis of diabetic retinopathy: A review | |
Mittal et al. | Computerized retinal image analysis-a survey | |
Gharaibeh et al. | A hybrid svm naïve-bayes classifier for bright lesions recognition in eye fundus images | |
Yu et al. | Fast vessel segmentation in retinal images using multi-scale enhancement and second-order local entropy | |
Soomro et al. | Contrast normalization steps for increased sensitivity of a retinal image segmentation method | |
Kipli et al. | A review on the extraction of quantitative retinal microvascular image feature | |
Akil et al. | Detection of retinal abnormalities in fundus image using CNN deep learning networks | |
Jan et al. | Retinal image analysis aimed at blood vessel tree segmentation and early detection of neural-layer deterioration | |
Saranya et al. | A novel approach for the detection of new vessels in the retinal images for screening diabetic retinopathy | |
Rekhi et al. | Automated detection and grading of diabetic macular edema from digital colour fundus images | |
Rodrigues et al. | Retinal vessel segmentation using parallel grayscale skeletonization algorithm and mathematical morphology | |
Singh et al. | A new morphology based approach for blood vessel segmentation in retinal images | |
Singh et al. | Features fusion based novel approach for efficient blood vessel segmentation from fundus images. | |
Mane et al. | Progress towards automated early stage detection of diabetic retinopathy: Image analysis systems and potential | |
Mendonça et al. | Segmentation of the vascular network of the retina | |
Fraz et al. | Retinal vessel extraction using first-order derivative of Gaussian and morphological processing | |
Zardadi et al. | Unsupervised segmentation of retinal blood vessels using the human visual system line detection model | |
Patil et al. | Automated macula proximity diagnosis for early finding of diabetic macular edema | |
Fraz et al. | Computer vision algorithms applied to retinal vessel segmentation and quantification of vessel caliber | |
Ramasubramanian et al. | A novel efficient approach for the screening of new abnormal blood vessels in color fundus images | |
Hussain | Optic nerve head segmentation using genetic active contours |