0000000000785502

AUTHOR

Prasanna Porwal

0000-0003-2268-7504

showing 3 related works from this author

Retinal vasculature segmentation and measurement framework for color fundus and SLO images

2020

Abstract The change in vascular geometry is an indicator of various health issues linked with vision and cardiovascular risk factors. Early detection and diagnosis of these changes can help patients to select an appropriate treatment option when the disease is in its primary phase. Automatic segmentation and quantification of these vessels would decrease the cost and eliminate inconsistency related to manual grading. However, automatic detection of the vessels is challenging in the presence of retinal pathologies and non-uniform illumination, two common occurrences in clinical settings. This paper presents a novel framework to address the issue of retinal blood vessel detection and width me…

business.industryComputer scienceBiomedical EngineeringRetinalVascular geometryFundus (eye)Scanning laser ophthalmoscopychemistry.chemical_compoundchemistryIterative thresholdingAutomatic segmentationGraph (abstract data type)SegmentationComputer visionArtificial intelligencebusinessBiocybernetics and Biomedical Engineering
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Retinal Fundus Multi-Disease Image Dataset (RFMiD): A Dataset for Multi-Disease Detection Research

2021

The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. Early detection and diagnosis of ocular pathologies would enable forestall of visual impairment. One challenge that limits the adoption of computer-aided diagnosis tool by ophthalmologists is the number of sight-threatening rare pathologies, such as central retinal artery occlusion or anterior ischemic optic neuropathy, and others are usually ignored. In the past two decades, many publicly available datasets of color fundus images have been collected with a primary focus on diabetic retinopathy, glaucoma, age-related macular…

Information Systems and Managementgenetic structuresVisual impairmentGlaucomaDiseaseFundus (eye)030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicinerare pathology detectionmedicineVision rehabilitationmulti-label classificationretinal fundus imagesbusiness.industryocular diseaseDiabetic retinopathyMacular degenerationmedicine.diseaselcsh:Zeye diseaseslcsh:Bibliography. Library science. Information resourcesComputer Science Applicationsclassification030221 ophthalmology & optometryOptometryCentral retinal artery occlusionsense organsmedicine.symptombusinessInformation SystemsData
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An Electrooculography based Human Machine Interface for wheelchair control

2019

International audience; This paper presents a novel single channel Electrooculography (EOG) based efficient Human–Machine Interface (HMI) for helping the individuals suffering from severe paralysis or motor degenerative diseases to regain mobility. In this study, we propose a robust system that generates control command using only one type of asynchronous eye activity (voluntary eye blink) to navigate the wheelchair without a need of graphical user interface. This work demonstrates a simple but robust and effective multi-level threshold strategy to generate control commands from multiple features associated with the single, double and triple voluntary eye blinks to control predefined action…

Information transfermedicine.diagnostic_testbusiness.industryComputer scienceInterface (computing)0206 medical engineeringControl (management)Biomedical Engineering02 engineering and technologyElectrooculographyHuman Machine InterfaceEOG controlled wheelchairSingle channel BMI020601 biomedical engineeringWheelchairAssistive technologyAsynchronous communication0202 electrical engineering electronic engineering information engineeringmedicine[SDV.IB]Life Sciences [q-bio]/Bioengineering020201 artificial intelligence & image processingbusinessSimulationCommunication channelGraphical user interfaceBiocybernetics and Biomedical Engineering
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