Medical imaging plays the vital role in diagnosis of abnormalities. Periodontitis is a common chronic inflammatory disease damaging the soft tissue that untreated can lead to loss of bone, which supports the teeth. The severity of periodontitis is correlated to pocket depth in alveolar area. Even if analyses of the pocket depth can be manually performed, an automatic assistive tool can drastically help radiologists conduct more accurate analyses. In the proposed research, image processing algorithms were developed to compute pocket depth and diagnose the periodontitis. Radiologists manually segmented 350 panoramic radiographic images, dividing them into normal and periodontitis. The same dataset is used in our work to validate the Classification algorithm. The images are preprocessed with median filter and histogram equalization to improve the contrast and then segmented using two‐dimensional‐Otsu thresholding method into teeth and bony area in the mandibular region. Normal pocket depth of 3 mm as reported by American Academy of Periodontology is equivalently converted to pixel height in the radiographic images. Based on this pocket depth rule based classification method classifies the images into normal and periodontitis. The proposed work achieved 91.34% accuracy, 92.8% sensitivity, and 95.47% F‐score in classifying the dental panoramic radiography.
Wireless sensor networks consist of number of sensor nodes widely distributed in particular region to communicate and sharing the environmental information and also these data’s are stored in central location for further data prediction. Such nodes are susceptible to cloning attack where the adversary captures a node, replicates with the same identity as that of the captured node and deploys the clone back into the network, causing severe harm to the network. Hence to thwart such attacks, a distributed detection protocol is used with initiator-observer-inspector roles assigned randomly for the nodes to witness the clone and thereby broadcast the evidence through a balanced overlay network. Use of such balanced network provides high security level and reduces the communication cost when compared to other overlay networks with a reasonably less storage consumption.
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