Search results for "Retinal Images"

showing 8 items of 8 documents

Accurate estimation of retinal vessel width using bagged decision trees and an extended multiresolution Hermite model.

2012

We present an algorithm estimating the width of retinal vessels in fundus camera images. The algorithm uses a novel parametric surface model of the cross-sectional intensities of vessels, and ensembles of bagged decision trees to estimate the local width from the parameters of the best-fit surface. We report comparative tests with REVIEW, currently the public database of reference for retinal width estimation, containing 16 images with 193 annotated vessel segments and 5066 profile points annotated manually by three independent experts. Comparative tests are reported also with our own set of 378 vessel widths selected sparsely in 38 images from the Tayside Scotland diabetic retinopathy scre…

Accurate estimationComputer scienceStability (learning theory)Decision treeHealth Informaticscomputer.software_genreSensitivity and SpecificityPattern Recognition AutomatedSet (abstract data type)Parametric surfaceImage Interpretation Computer-AssistedHumansRadiology Nuclear Medicine and imagingFluorescein AngiographyHermite polynomialsDiabetic RetinopathySettore INF/01 - InformaticaRadiological and Ultrasound TechnologyReproducibility of ResultsRetinal VesselsImage EnhancementComputer Graphics and Computer-Aided DesignData setComputer Vision and Pattern RecognitionData miningRetinal images Vessel width Multiresolution Hermite model Ensembles of bagged decision trees Medical image analysiscomputerAlgorithmsTest dataRetinoscopyMedical image analysis
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FABC: Retinal Vessel Segmentation Using AdaBoost

2010

This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…

Databases FactualComputer scienceFeature vectorFeature extractionNormal DistributionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingModels BiologicalEdge detectionArtificial IntelligenceImage Processing Computer-AssistedHumansSegmentationComputer visionAdaBoostFluorescein AngiographyElectrical and Electronic EngineeringTraining setPixelContextual image classificationSettore INF/01 - Informaticabusiness.industryReproducibility of ResultsRetinal VesselsWavelet transformBayes TheoremPattern recognitionGeneral MedicineImage segmentationComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONROC CurveTest setAdaBoost classifier retinal images vessel segmentationArtificial intelligencebusinessAlgorithmsBiotechnology
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VAMPIRE: Vessel assessment and measurement platform for images of the REtina

2011

We present VAMPIRE, a software application for efficient, semi-automatic quantification of retinal vessel properties with large collections of fundus camera images. VAMPIRE is also an international collaborative project of four image processing groups and five clinical centres. The system provides automatic detection of retinal landmarks (optic disc, vasculature), and quantifies key parameters used frequently in investigative studies: vessel width, vessel branching coefficients, and tortuosity. The ultimate vision is to make VAMPIRE available as a public tool, to support quantification and analysis of large collections of fundus camera images.

Opthalmology; image processing; retinaEngineeringVesselgenetic structuresOpthalmologyImage processingRetinal ImagesRetinaRetina; Image; VesselSoftwareMedical imagingmedicineHumansSegmentationComputer visionRetinaSettore INF/01 - Informaticabusiness.industryVampireRetinal VesselsImage segmentationeye diseasesimage processingFractalsVAMPIREmedicine.anatomical_structureImageArtificial intelligenceAdvanced image processing and mathematical modeling techniquesbusinessOptic disc2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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A Comparative Study on Feature Selection for Retinal Vessel Segmentation Using FABC

2009

This paper presents a comparative study on five feature selection heuristics applied to a retinal image database called DRIVE. Features are chosen from a feature vector (encoding local information, but as well information from structures and shapes available in the image) constructed for each pixel in the field of view (FOV) of the image. After selecting the most discriminatory features, an AdaBoost classifier is applied for training. The results of classifications are used to compare the effectiveness of the five feature selection methods.

PixelSettore INF/01 - InformaticaComputer sciencebusiness.industryFeature vectorRetinal images vessel segmentation AdaBoost classifier feature selection.ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionFeature selectionFeature (computer vision)SegmentationComputer visionArtificial intelligenceHeuristicsbusinessFeature detection (computer vision)
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Color difference threshold of chromostereopsis induced by flat display emission

2015

The study of chromostereopsis has gained attention in the backdrop of the use of computer displays in daily life. In this context, we analyze the illusory depth sense using planar color images presented on a computer screen. We determine the color difference threshold required to induce an illusory sense of depth psychometrically using a constant stimuli paradigm. Isoluminant stimuli are presented on a computer screen, which stimuli are aligned along the blue–red line in the computer display CIE xyY color space. Stereo disparity is generated by increasing the color difference between the central and surrounding areas of the stimuli with both areas consisting of random dots on a black backgr…

Point spread functionChromostereopsisstereo disparityColor differencePixelgenetic structuresbusiness.industrylcsh:BF1-990eye chromatic aberrationsContext (language use)Pupilfusion of retinal imageslcsh:PsychologyPlanarperception thresholdColor chartPsychologychromostereopsisComputer visionArtificial intelligenceStereodisparitybusinessPsychologyGeneral PsychologyOriginal ResearchFrontiers in Psychology
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Semi-automatic registration of retinal images based on line matching approach

2013

Accurate retinal image registration is essential to track the evolution of eye-related diseases. We propose a semiautomatic method based on features relying upon retinal graphs for temporal registration of retinal images. The features represent straight lines connecting vascular landmarks on the retina vascular tree: bifurcations, branchings, crossings, end points. In the built retinal graph, one straight line between two vascular landmarks indicates that they are connected by a vascular segment in the original retinal image. The locations of the landmarks are manually extracted to avoid the information loss due to errors in a retinal vessels segmentation algorithms. A straight line model i…

Semi-automatic registration of retinal images based on line matching approachGround truthSettore INF/01 - InformaticaMatching (graph theory)Computer sciencebusiness.industryFeature extractionImage registrationRetinalSimilarity measureTree (graph theory)chemistry.chemical_compoundchemistrySegmentationComputer visionArtificial intelligencebusinessProceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems
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Graph-based minimal path tracking in the skeleton of the retinal vascular network

2012

This paper presents a semi-automatic framework for minimal path tracking in the skeleton of the retinal vascular network. The method is based on the graph structure of the vessel network. The vascular network is represented based on the skeleton of the available segmented vessels and using an undirected graph. Significant points on the skeleton are considered nodes of the graph, while the edge of the graph is represented by the vessel segment linking two neighboring nodes. The graph is represented then in the form of a connectivity matrix, using a novel method for defining vertex connectivity. Dijkstra and Floyd-Warshall algorithms are applied for detection of minimal paths within the graph…

Settore INF/01 - Informaticabusiness.industryComputer sciencePath trackingGraph theoryImage segmentationGraph bandwidthRetinal Images Graphs Dijkstra Floyd-WarshallGraph (abstract data type)Computer visionArtificial intelligencebusinessBeta skeletonDijkstra's algorithmAlgorithmRandom geometric graphMathematicsofComputing_DISCRETEMATHEMATICS2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS)
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Statistical atlas based exudate segmentation

2013

International audience; Diabetic macular edema (DME) is characterized by hard exudates. In this article, we propose a novel statistical atlas based method for segmentation of such exudates. Any test fundus image is first warped on the atlas co-ordinate and then a distance map is obtained with the mean atlas image. This leaves behind the candidate lesions. Post-processing schemes are introduced for final segmentation of the exudate. Experiments with the publicly available HEI-MED data-set shows good performance of the method. A lesion localization fraction of 82.5% at 35% of non-lesion localization fraction on the FROC curve is obtained. The method is also compared to few most recent referen…

[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]exudate segmentation[ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processing[INFO.INFO-IM]Computer Science [cs]/Medical Imaging[INFO.INFO-IM] Computer Science [cs]/Medical Imagingstatistical retinal atlasretinal images registration
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