Implementation of an Efficient Microbial Medical Image Retrieval System Applying Knowledge Databases

Yongwon Shin; Bongoh Goo

This study is to design and implement an efficient microbial medical image retrieval system based on knowledge and content of them which can make use of more accurate decision on colony as well as efficient education for new technicians. For this, we first address overall inference to set up flexible search path using rule-base in order to reduce time required original microbial identification by searching the fastest path of microbial identification phase based on heuristics knowledge. Next, we propose a color feature extraction method, which is able to extract color feature vectors of visual contents from a given microbial image based on especially bacteria image using HSV color model. In addition, for better retrieval performance based on large microbial databases, we present an integrated indexing technique that combines with B+-tree for indexing simple attributes, inverted file structure for text medical keywords list, and scan-based filtering method for high dimensional color feature vectors. Finally, the implemented system shows the possibility to manage and retrieve the complex microbial images using knowledge and visual contents itself effectively. We expect to decrease rapidly learning time for elementary technicians by well organizing knowledge of clinical fields through proposed system.

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* 2021년 이후 발행 논문의 참고문헌은 현재 구축 중입니다.

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