Automatic Diagnosis of Diabetic Retinopathy Using Morphological Operations

Diabetic retinopathy is diabetic eye disease or a sight threatening complication (one of the major cause of blindness) for the person suffering from diabetes which causes progressive loss to the retina, in which retina of the eye is affected because the capillaries of the retina are damaged. Diabetic Retinopathy is unpredictable at early stage, it is only predictable in advanced stage when diabetic patient suffers from loss of vision due to leakage of lipid, blood vessels bursts and there is formation of new fragile blood vessels which blocks the blood supply to retina. Diabetic Retinopathy include Microaneurysm, hemorrhage and exudates. However, early detection and treatment is most important that can reduce the chances of occurrences of blindness about 95%. To analyze Microaneurysm and hemorrhage as early stages of DR is a challenging task for Ophthalmologists to prevent vision loss. Automatic analysis of Diabetic Retinopathy helps in preventing vision loss. Our proposed method is based on automatic detection of hemorrhage using colorful fundus images. In proposed work we have used supervised learning to classify the data as hemorrhage and without hemorrhage with SVM classifier. To find hemorrhage and its severity, we have extracted statistical features (including standard deviation, energy, entropy and contrast of an image), used classification approach and then segmentation methods. After feature detection, Morphological Operations are applied to detect blood vessels and hemorrhage detection with help of segmentation technique. Here the threshold optimization, Grey Wolf Optimization (GWO) techniques are used in our proposed work for getting maximum accuracy, sensitivity and specificity performance metrics

Development of an Arduino Based Device for Early Detection of Gas Leakage in Hospitals & Industries

Leakage of gases in a system makes infrastructures and users vulnerable, it can occur due to its environmental conditions or old groundwork. Hospitals and industries where many types of gases are used like nitrogen, mono oxide, due to small amount of concentration in air can cause toxicity whereas detection of small amount of gas at its initial stage is very difficult task. Many systems have been developed which were failed in past to give accuracy in its implementation. In this research a portable detection system for the small leakage of gases has been developed, gas sensor (MQ-2) is used to find leakage when it is at its initial phase. The sensor and transmitting module senses the change in level of gas by using a sensing circuit. When a concentration of gas reach at a specified threshold level it will activate an alarm and sends a text massage to receiving module. The proposed system works well in hospitals, home, and industries

Simulation of Low-Frequency Sonophoretic Piezoelectric Transducer Applied over Human Skin

Sonophoresis is the process that involves the passage of drug molecules through the skin under ultrasonic stimulation. Drugs with a molecular weight greater than 500 daltons require some kind of stimulus to catalyze their penetration into the skin. Low-frequency sonophoresis, i.e., applying low-frequency (20–100 kHz) ultrasonic waves, is one of the active methods of stimulation used in transdermal drug delivery. The aim of this research is to explore the possibility of achieving high enough acoustic pressures inside human skin using a single-element piezoelectric transducer required to realize the transdermal delivery of drugs with a high molecular weight. Therefore, this paper presents a design and simulation of a single-element transducer to find voltage versus sound pressure levels (SPLs), as well as frequency response curves for low-frequency sonophoresis on human skin. A piezoelectric transducer composed of PZT-5H placed over human skin was simulated by combining the pressure acoustic module, solid mechanics, and electrostatic modules of the simulation tool. The presented simulation applies sinusoidal excitation to a PZT-5H-based transducer. The peak voltage and the frequency of the input are varied to study the resulting variations in acoustic pressure and SPL inside the human skin. Measurements of acoustic pressure are taken 0.1 mm deep into the human skin. The peak acoustic pressure increases linearly from 0.072 Pa to 0.72 Pa as the peak applied voltage increases from 1 mV to 10 mV. The peak acoustic pressure increases exponentially from 0.2 mPa to 5 mPa as the frequency varies from 20 kHz to 100 kHz for a constant peak voltage of 1 mV. The SPL achieved at 880 kHz is 186 dB, which is suitable for drug delivery in some areas of medicine, such as ophthalmology