BACKGROUND: Content-based medical image retrieval involves multiple domains.Due to different imaging principles of various medical images,there are differences in color,texture,and shape,which should be resolved.OBJECTIVE: As in content-based medical image retrieval system,feature extraction from image is very difficult and the retrieval is very time-consuming,a similar image retrieval method based on graph-cuts and rough sets is proposed.METHODS: In order to overcome the defects that graph-cuts is only suitable for small image end easily leads to a small cut-sets,a clustering was applied to image,and the Gomory-Hu cuts tree of image was established.An image feature library was built by removing the edges of Gomory-Hu cuts tree for the value of cut.Reduction of features in library was obtained based on rough sets and the number of features in similar compare decrease.This method was applied to retrieve brain tumor image in MRI brain image database.RESULTS AND CONCLUSION: Results show that this method can effectively retrieve brain tumor images in the library.The average retrieval precision rate and the average recall rates were 78.4% and 62.9%,respectively.

Hepatic stellate cell(HSC)activation is a key link in the development of liver fibrosis.The metabolic reprogramming of activated HSC has become a hot topic in current research,especially the change of glycolysis is an important factor in regulating HSC activation.Based on the metabolic reprogramming in the process of HSC activation,this paper expounds the mechanism of regulating HSC activation and liver fibrosis through glycolysis,and reviews the research progress of traditional Chinese medicine and its active ingredients in regulating HSC glycolysis to prevent and treat liver fibrosis.Liver fibrosis is a complex pathological process involving multiple factors and pathways.From the perspective of regulating the glycolysis of activated HSC,it can provide a new idea for the development of anti-liver fibrosis drugs.