Abstract
Feature-Based Medical Image Retrieval (FBMIR) systems are exploited to retrieve useful contents from a massive number of medical images. A novel technique for image retrieval in medical field with Grey Wolf Optimization-Support Vector Machine (GWO-SVM) is proposed. CT scan images are used as input images. Firstly, the images are considered for extraction, where the scaling & rotation invariant features are taken out using corresponding colour moments. Secondly, texture features are taken out using dominant GLCM features that comprise of correlation, contrast, energy, etc. Feature mapping is performed with the help of Bag of Words (BoW). In the existing system, the images are first retrieved and then classified. In the proposed method, the time of image retrieval is more since it has to search the whole database for performing the retrieval. Moreover, the retrieval rates obtained by the existing methods are not satisfactory. The novelty of proposed paper gives GWO-SVM technique that initially classifies the class to which the query image belongs. Further the retrieval task are organized only from the Database of query images. The GWO algorithm gives the solved and optimized parameters are given a clear optimized value for the SVM classifier. Thus, by finding the retrieval rate after performing the classification, it is evident that output retrieval rate is large when compared to existing methods. The fundamental performance metrics like accuracy, sensitivity and specificity are taken into comparison. The proposed techniques provides higher accuracy 97.3% than the performance of BoW and Grey Wolf Optimization (GWO).
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Renita, D.B., Christopher, C.S. Novel real time content based medical image retrieval scheme with GWO-SVM. Multimed Tools Appl 79, 17227–17243 (2020). https://doi.org/10.1007/s11042-019-07777-w
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DOI: https://doi.org/10.1007/s11042-019-07777-w