Author(s) :
J. Anto Germin Sweeta, B. Sivagami
Conference Name :
7th International Conference on Recent Innovations in Computer and Communication (ICRICC 23)
Abstract :
Content Based Image Retrieval (CBIR) has been one on the most vivid research areas in the field of computer vision over the decades. The availability of large and steadily growing amounts of visual and multimedia data, and the development of the Internet underline the need to create thematic access methods that are more than simple text based queries or requests based on matching exact database fields. Content based Image Retrieval (CBIR) aids radiologist to identify similar medical images in recalling previous cases during diagnosis. Although several algorithms have been introduced to extract the content of the medical images, the process is still a challenge due to the nature of the feature itself where most of them are extracted in low level form. In addition to the dimensionality reduction problem caused by the low level features, current features are also insufficient to convey the semantic meaning of the images. This article gives an overview of available literature in the field of content based access to medical image data and on the technologies used in the field. The shortcomings of the current CBIR systems are discussed and future directions toward context based medical image retrieval are expressed.
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