Search results for "Predictive evaluation diseases"

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A visual framework to create photorealistic retinal vessels for diagnosis purposes

2020

The methods developed in recent years for synthesising an ocular fundus can be been divided into two main categories. The first category of methods involves the development of an anatomical model of the eye, where artificial images are generated using appropriate parameters for modelling the vascular networks and fundus. The second type of method has been made possible by the development of deep learning techniques and improvements in the performance of hardware (especially graphics cards equipped with a large number of cores). The methodology proposed here to produce high-resolution synthetic fundus images is intended to be an alternative to the increasingly widespread use of generative ad…

PLUS DISEASEData augmentationFundus OculiComputer scienceCOMPUTER-AIDED DIAGNOSISIMAGESSEGMENTATIONComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHealth InformaticsSynthetic retinal imageFundus (eye)Fundus image analysisStatistical featuresTORTUOSITY03 medical and health sciences0302 clinical medicineImage Processing Computer-AssistedComputer vision030212 general & internal medicineGraphics030304 developmental biologyGraphical user interfaceSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni0303 health sciencesSettore INF/01 - Informaticabusiness.industryDeep learningRetinal VesselsReal imageComputer Science ApplicationsPredictive evaluation diseasesFILTERA priori and a posterioriArtificial intelligencebusinessSYSTEMJournal of Biomedical Informatics
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Retinal image synthesis through the least action principle

2020

Eye fundus image analysis is a fundamental approach in medical diagnosis and follow-up ophthalmic diagnostics. Manual annotation by experts needs hard work, thus only a small set of annotated vessel structures is available. Examples such as DRIVE and STARE include small sets for training images of fundus image benchmarks. Moreover, there is no vessel structure annotation for a number of fundus image datasets. Synthetic images have been generated by using appropriate parameters for the modeling of vascular networks or by methods developing deep learning techniques and supported by performance hardware. Our methodology aims to produce high-resolution synthetic fundus images alternative to the…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticapredictive evaluation diseasesComputer sciencebusiness.industryDeep learningComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFundus (eye)Real imageSmall setPrinciple of least actionImage (mathematics)fundus image analysisAnnotationComputer visionArtificial intelligenceMedical diagnosisbusinessstatistical featuressynthetic retinal imagedata augmentation2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)
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