Automatic Blood Vessel Extraction of Fundus Images Employing Fuzzy Approach

Diabetic Retinopathy is a retinal vascular disease that is characterized by progressive deterioration of blood vessels in the retina and is distinguished by the appearance of different types of clinical lesions like microaneurysms, hemorrhages, exudates etc. Automated detection of the lesions plays significant role for early diagnosis by enabling medication for the treatment of severe eye diseases preventing visual loss. Extraction of blood vessels can facilitate ophthalmic services by automating computer aided screening of fundus images. This paper presents blood vessel extraction algorithms with ensemble of pre-processing and post-processing steps which enhance the image quality for better analysis of retinal images for automated detection. Extensive performance based evaluation of the proposed approaches is done over four databases on the basis of statistical parameters. Comparison of both blood vessel extraction techniques on different databases reveals that fuzzy based approach gives better results as compared to Kirsch’s based algorithm. The results obtained from this study reveal that 89% average accuracy is offered by the proposed MBVEKA and 98% for proposed BVEFA

Retinal blood vessel localization to expedite PDR diagnosis

Ophthalmologist relies on the retinal fundus image segmentation for accurate diagnosis of Diabetic Retinopathy caused due to prolonged deterioration in retinal blood vessels. Blood vessel and optical disc localization determines the vascular alterations helpful in identifying retinal diseases with accurate identification of pathologies like microaneurysms and exudates. This work comprises evaluation of proposed Optical Disc Segmentation and blood vessel localization techniques followed by a statistical analysis using three fractal dimensions; box count, information and correlation. Fractal dimensions explored are beneficial for Proliferative Diabetic Retinopathy (PDR) diagnosis as its value for vascular structures increases with increasing level of PDR. Two benchmark fundus image databases, DRIVE and STARE were evaluated by utilizing shape and fractal features for performance validation and average accuracies of 96.79% and 95.68% were achieved for extracted blood vessels using proposed approach

Semiautomatic detection of cardiac diseases employing dual tree complex wavelet transform

Electrocardiogram (ECG) contains lot of information which can be utilized for a mechanism to detect cardiac abnormalities. The ECG signal is too sensitive to various types of noises as it is of low frequency and has weak amplitude, these noises reduce the diagnostic accuracy and may lead to the incorrect decision of the clinician. So, denoising of ECG signal is an essential requirement for an accurate detection of Heart disease. In this paper, a Dual-Tree Complex Wavelet Transform technique (DTCWT) is presented to denoise the noisy ECG signal and to extract the Principal features followed by implementation of Peak Detection Algorithm. The performance is evaluated on the basis of performance metrics and an increase in SNR is achieved using the technique. With the proposed technique, calculated heart rate is in consensus with the gold standard of the various bench mark databases used and accurate heart disease was determined

On the use of varied natural fibers as sustainable sources to tailor highly efficient geopolymer composite materials

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Bouveret’s Syndrome: 64-Slice CT Diagnosis and Surgical Management—A Case Report

Gastric outlet obstruction caused by duodenal impaction of a large gallstone migrated through a cholecystoduodenal fistula has been referred to as Bouveret’s syndrome. We present a case of gallstone-induced duodenal obstruction in an elderly female patient, diagnosed on a 64-slice MDCT scanner. One-stage surgery, that is, stone removal and cholecystectomy, was performed resulting in relief of obstruction and complete cure. Clinical features, multidetector computed tomography (MDCT) findings, and surgical management are discussed

Development of low cost set up for anodic bonding and its characterization

738-743A low cost experimental set- up for anodic bonding has been developed indigenously in the college laboratory and glass silicon bonding parameters characterized. Anodic bonding between silicon and glass substrates has been characterized in detail. The effects of magnitude of the applied voltage on the time required for complete bonding have also been investigated. The effect of voltage, point contact, bond strength and electrostatic force in anodic wafer bonding process has also been analyzed. The glass to silicon bonding at 1150V, 450ºC has been successfully performed. This enables simple, but highly accurate, alignment of pre-patterned glass and silicon wafers. Fabricated devices have wide benefits like glass transparency at optical wavelength