Comparative Study of Image Fusion Techniques in Treatment Planning

The process by which different images or information from multiple images are combined is termed as
Image fusion which is achieved by applying a sequence of operators on the images. Recently, a
number of image fusion techniques have been developed. This chapter presents a review on the main
categories of image fusion namely spatial domain technique, transform domain technique and
statistical domain fusion technique. This chapter also reviews on the importance of image fusion
techniques in treatment planning. Image Fusion is one of the latest fields adopted to solve the
problems of digital image; image fusion produces high-quality images which contains additional
information for the purposes of interpretation, classification, segmentation and compression, etc. The
principle requirement of the fusion process is to identify the most significant features in the input
images and to transfer them without loss of detail into the fused image. Image Fusion finds its
application in vast range of areas. It is used for medical diagnostics and treatment. This chapter
presents a brief description of some of the extensively used image fusion techniques for treatment
planning. Comparison of all available image fusion techniques concludes a better approach for future
research on image fusion.