A Survey Paper on Content based Medical Image Retrieval for Reducing Semantic Gap

SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 01, FEB 2018 PP.(257-264)
Abstract– Content-based image retrieval is a search technique for retrieving required images from the database which is similar to the query image. CBIR retrieving the images based on visual features like color, texture, and shape. In recent years, one important focus of medical informatics research has been reducing the semantic gap which is the difference between the human description of the image and the system description of the image. To reduce the semantic gap, CBIR uses machine learning algorithms for feature extraction and selection. This survey covers the approaches for feature extraction and selection, different distance measures for measuring the similarity of the images and the techniques for reducing the semantic gap. In addition to these, various data sets used in CBIR and the performance measures, are also addressed.
Index Terms – Content-based image retrieval, Semantic gap, Feature extraction, precision and Recall.
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G. Thenmozhi , S. Kumaresan
Government College of Technology,
Coimbatore, India.
then21.gct@gmail.com,
sukumaresan@gct.ac.in

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