Medical image processing based on multidimensional wavelet transforms - Advantages and trends

The quality of medical images is very important in clinical use, such as clinical diagnosis, pathology analysis, etc. This paper presents a brief survey of the advantages and trends of medical image processing techniques based on multidimensional wavelet transforms as well as their combinations with other methods, which model each coefficient set as a tensor. Unlike the classical wavelet decompositions wavelet tensor modifications has only one parameter to be tuned, which makes the computing easier to use in various medical processing methods such as noise reduction, compression, segmentation, classification, medical image fusion. These methods can be very useful for multidimensional images such as MRI and CT data or for integration and analysis of many types of medical image data.