Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6921128 | Computers in Biology and Medicine | 2015 | 21 Pages |
Abstract
Diabetic Macular Edema (DME) is caused by accumulation of extracellular fluid from hyperpermeable capillaries within the macula. DME is one of the leading causes of blindness among Diabetes Mellitus (DM) patients. Early detection followed by laser photocoagulation can save the visual loss. This review discusses various imaging modalities viz. biomicroscopy, Fluorescein Angiography (FA), Optical Coherence Tomography (OCT) and colour fundus photographs used for diagnosis of DME. Various automated DME grading systems using retinal fundus images, associated retinal image processing techniques for fovea, exudate detection and segmentation are presented. We have also compared various imaging modalities and automated screening methods used for DME grading. The reviewed literature indicates that FA and OCT identify DME related changes accurately. FA is an invasive method, which uses fluorescein dye, and OCT is an expensive imaging method compared to fundus photographs. Moreover, using fundus images DME can be identified and automated. DME grading algorithms can be implemented for telescreening. Hence, fundus imaging based DME grading is more suitable and affordable method compared to biomicroscopy, FA, and OCT modalities.
Keywords
FCMCNVHMADMECDRGDDANFISCWSSVDPPVGLCMLBPAMDFLDAk-NNEHDGCLONLCMTDWTFAFGCCGMMHRFETDRSCSMECRVONPDRRNFLMicroaneurysmsRtaPDRLMESRDKLDPolarization sensitiveFundus imagingGrey level co-occurrence matrixDT-CWTInstantaneous amplitudeEdge histogram descriptorFourier domainHOSAUCNaïve BayesChoroidal neovascularizationRgbrTMARIACMEfluorescein angiographyDiabetic macular edemaclinically significant macular edemaMacular edemacystoid macular edemapositive predictive valueHard exudatesGenetic algorithmLocal Binary PatternFAZstandard deviationCentral retinal vein occlusionOctFractal dimensionFARParticle swarm optimizationPSOBiomicroscopyDiscrete wavelet transformsingular value decompositionanalysis of varianceANOVAComputer-aided diagnosisComputer aided diagnosisDual tree complex wavelet transformOptical coherence tomographySerous retinal detachmentVisual acuityHaemorrhagesearly treatment diabetic retinopathy studyDiabetes mellitusoptic diskDrivediabetic retinopathyProliferative diabetic retinopathyNon-proliferative diabetic retinopathyage-related macular degenerationAdaptive neuro-fuzzy inference systemNeural networkretinal thicknessCentral macular thicknessCADHigher order spectraFourier spectrumOptic nerveFuzzy C-Meansconfidence intervalfundus autofluorescenceinstantaneous frequencyred green bluedisc diameterouter nuclear layerganglion cell layerRetinal nerve fiber layerSupport vector machineSVMganglion cell complexGaussian mixture modelamplitude modulationFrequency modulationfoveal avascular zoneGabor waveletNeovascularizationCup-to-disc ratioCotton wool spotshigh-definition
Related Topics
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Authors
Muthu Rama Krishnan Mookiah, U. Rajendra Acharya, Hamido Fujita, Jen Hong Tan, Chua Kuang Chua, Sulatha V. Bhandary, Augustinus Laude, Louis Tong,