Learning Based Combining Different Features for Medical Image Retrieval

In this paper, authors propose a new learning based method for medical image retrieval which is based on fusing different features by linearly combining different similarities. Considering the abundant classes of medical images, this paper avoid to train a classifier for each class by using large amount training data. Instead, by using optimization method to combine different features´ similarity, new method can get good performance while has no much training computation. Experimental results show that the algorithm has potential practical values for clinical routine application.