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Content Based Image Retrieval Using Nearest Neighbour and Hybrid KNNSVM Methods to Diagnose MR Images

Dr.A.Kannan

The Content Based Image Retrieval (CBIR) is a popular and powerful technology which is designed to retrieve the desired target image from the large collection of images based on the contents of the given query image. In this paper, the CBIR is designed to support the medical field toretrieve similar and dissimilar conditioned Magnetic Resonance (MR) Images to aid for analysing the condition of brain tumour of a patient using Hybrid K-Nearest NeighbourSupport Vector Machine (HKNNSVM) and Nearest Neighbour (NN) algorithms. All we aware that the field of medical plays a vital role in every country and day to day improvements are being concentrated at regular intervals to save the life of the patients from very crucial diseases. Especially, Magnetic Resonance Image (MRI)dominates medical field to certain extend to identify and examine the patient’s critical problems in an effective and efficient manner. Every day, large numbers of MR Images are being generated and stored in the image database. If these images are processed in a right way, it will reveal useful information to the physicians to take immediate suitable remedial actions for the patient concerned very earlier.

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学术钥匙
研究圣经
引用因子
宇宙IF
参考搜索
哈姆达大学
世界科学期刊目录
学者指导
国际创新期刊影响因子(IIJIF)
国际组织研究所 (I2OR)
宇宙

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