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Entomophagy insects are local food/ feed in most parts of the North Malay Archipelago. These insects are a standard natural resource that provides food and economical safety to most ethnic groups of Eastern Himalayas. Entomophagy not only supports the nutritional food security, but also provides the family livelihood to the tribal populations during difficult times of the year. Since, edible insects are great source of supplemental food item that would meet the people’s present and future need, they’re preferred by tribal communities as eggs, nymphs, larvae, pupa and adults insects, and eaten as fried, cooked, roasted or are even consumed as raw repeatedly. In India, a complete of 245 species, 50 families and 10 orders of edible insects have been recorded so far as food and it’s mostly practiced in eight North Eastern States of India. Among the edible species of insects, biggest consumption is of coleopteran species with 24.69%, followed by Hemiptera (22.63%), Orthoptera (17.28%), Hymanoptera (13.17%), Odonata (10.70%), Lepidoptera (5.35%), Isoptera (2.88%), Dictyoptera (2.06%) and therefore the least were Diptera (0.41%) and Ephimeroptera (0.82%). Study of edible insect in India evolved the uncharted natural resources of north-east region and medicinal, traditional beliefs of tribal people. This review paper discuss about the common edible insects consumed by different ethnic and tribal communities in North-east India.

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Problem statement: With increasing bandwidth, digital medical image storage and transmission is a boon to patients and health professionals alike. Medical images are available instantly and avoid the need to carry the data physically. Popular imaging techniques extensively used in medicine include X-Ray, Magnetic Resonance Imaging (MRI), Ultrasound and Computed Tomography (CT). The images produced from the above techniques can be segregated into spatial regions with some regions more important for diagnosis compared to other regions. The region of interest for diagnosis is usually a small area compared to the whole image captured. Compression techniques play a very important role for fast and efficient transfer of medical images. Lossless compression techniques ensure no data loss but have the limitations of low compression rate. Lossy compression techniques on the other hand provide better compression ratios but the cost of wrong diagnosis is very high. In this study it is proposed to explore multiple compression techniques based on Region OF Interest (ROI). Approach: In this study a novel active contour method is proposed which is adaptive and marks the outer region of interest without edges. Based on the ROI, the active area of interest is compressed using lossless compression and the other areas compressed with lossy wavelet compression techniques. Results and Conclusion: Our proposed procedure was applied to different MRI images obtaining overall compression ratios of 70-80% without losing the originality in the ROI