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Design of Distribution Transformer Health Management System using IoT Sensors
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Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
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Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
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Volume - 2 | Issue - 2 | june 2020
Published
22 May, 2020
The detection of edges is the one of the important stage in the application, associated with the machine vision, computer vision and the image processing. It is most commonly and highly preferred in the area were the extraction or the detection of the attribute are necessary. As the manual methods of diagnosis in the medical images acquired from the CT (computed tomography) and the MRI (magnetic resonance images) are very tedious and as well as time consuming, the paper puts forth the methodology to detect the edges in the CT and the MRI by employing Gabor Transform as well as the soft and the hard clustering. This proposed method is highly preferred among the image with dynamic variations. The technique used in the paper is evaluated using 4500 instance of the MRI and 3000 instance of CT. The results on the basis of the figure of merit (FOM) and Misclassification rate (MCR) are compared with other standard approaches and the performance was evinced.
KeywordsHard and Soft clustering Edge detection Image Processing CT and MRI
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