ABSTRACT
Machine learning algorithm plays an important role in the medical imaging field, including computer-aided diagnosis, image segmentation, image registration, image-guided therapy and image classification. Recently, the application of machine learning techniques to medical image retrieval has received more attention. Due to the rapid development of computer technology, it is becoming more and more convenient to acquire, digitally store and transfer medical imagery. Nowadays, many hospitals need to manage several tera-bytes of medical image data each year. Therefore, categorization of medical images is becoming imperative for a variety of medical systems, especially in the application of digital radiology such as CAD and Case-based reasoning.
This chapter deals with semantic gap with different machine learning algorithms namely Support Vector Machine, Self Organizing Map, Relevance feedback and fuzzy for classification & retrieval of ultrasound liver images and future scope is also explained in detailed at the end.
