Medical Image Retrieval Based on Hilbert-Huang Transform

The approach of medical image decomposition and texture feature extraction based on Hilbert-Huang Transform(HHT),which can decompose the image into a set of functions denoted Intrinsic Mode Functions(IMF)and a residue,was presented.The extracted features were used for medical image retrieval.The Bidimensional Empirical Mode Decomposition(BEMD)method was used to decompose the medical image,the features extracted were the mean and standard deviation of the amplitude of the IMFs and their Hilbert transformations.Furthermore,according to the spatial relationship between local extrema points,a novel boundary processing approach based on clustering algorithm was proposed.In order to evaluate the proposed HHT-based feature,we also presented two multi-scale nonlinear texture features,which were multi-scale complexity and multi-scale fractal dimension feature.Preliminary comparision experimental results showed that the medical image retrieval results based on HHT were encouraged.