Content-based medical image retrieval is now getting more and more attention in the

world, a feasible and efficient retrieving algorithm for clinical endoscopic images is urgently

required. Methods: Based on the study of single feature image retrieving techniques, including color

clustering, color texture and shape, a new retrieving method with multi-features fusion and relevance

feedback is proposed to retrieve the desired endoscopic images. Results: A prototype system is set

up to evaluate the proposed method’s performance and some evaluating parameters such as the

retrieval precision & recall, statistical average position of top 5 most similar image on various features, etc.

are therefore given. Conclusions: The algorithm with multi-features fusion and relevance feedback

gets more accurate and quicker retrieving capability than the one with single feature image retrieving

technique due to its flexible feature combination and interactive relevance feedback.