V. Priya Govindasamy

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The widespread availability of electronic imaging devices throughout the medical community is leading to a growing body of research on image processing and analysis to diagnose retinal disease such as diabetic retinopathy (DR). Productive computer-based screening of large, at-risk populations at low cost requires robust, automated image analysis. In this(More)
PURPOSE To describe a novel computer-based image analysis method that is being developed to assist and automate the diagnosis of retinal disease. METHODS Content-based image retrieval is the process of retrieving related images from large database collections using their pictorial content. The content feature list becomes the index for storage, search,(More)
A total of 137 bacterial isolates from surface sterilized root, stem, and nodule tissues of soybean were screened for their antifungal activity against major phytopathogens like Rhizoctonia bataticola, Macrophomina phaseolina, Fusarium udam, and Sclerotium rolfsii. Nine bacterial endophytes suppressed the pathogens under in vitro plate assay. These were(More)
Diabetes has become an epidemic that is expected to impact 365 million people worldwide by 2025. Consequently, diabetic retinopathy is the leading cause of blindness in the industrialized world today. If detected early, treatments can preserve vision and significantly reduce debilitating blindness. Through this research we are developing and testing a(More)
In this work we report on a method for lesion segmentation based on the morphological reconstruction methods of Sbeh et. al. We adapt the method to include segmentation of dark lesions with a given vasculature segmentation. The segmentation is performed at a variety of scales determined using ground-truth data. Since the method tends to over-segment(More)
In this work we compare two methods for automatic optic nerve (ON) localization in retinal imagery. The first method uses a Bayesian decision theory discriminator based on four spatial features of the retina imagery. The second method uses a principal component-based reconstruction to model the ON. We report on an improvement to the model-based technique by(More)
Lowering of plant ethylene by deamination of its immediate precursor 1-aminocyclopropane-1-carboxylate (ACC) is a key trait found in many rhizobacteria. We isolated and screened bacteria from the rhizosphere of wheat for their ACC-degrading ability. The ACC deaminase gene (acdS) isolated from two bacterial isolates through PCR amplification was cloned and(More)
The enzyme 1-aminocyclopropane-1-carboxylate deaminase converts ACC, the precursor of the plant hormone ethylene to α-ketobutyrate and ammonium. The enzyme has been identified in few soil bacteria, and is proposed to play a key role in plant growth promotion. In this study, the isolates of plant growth promoting rhizobacteria were screened for ACC deaminase(More)
Ten mustard rhizobacterial isolates that utilize 1-aminocyclopropane-1-carboxylate (ACC) as sole nitrogen source were screened for plant growth-promoting traits. These isolates enhanced root elongation significantly and minimized ethylene synthesis in wheat seedlings under induced cadmium stress condition. The presence of acdS gene coding for ACC deaminase(More)
Culture supernatant of soybean nodule endophytic bacterium Paenibacillus sp strain HKA-15 showed the antifungal activity against Rhizoctonia bataticola, the causative agent of charcoal rot disease in soybean. The activity was detected only during the on set of stationary phase (24h post inoculation) in potato dextrose broth. The culture filtrate was(More)