Abstract
Medical image processing plays an important role in healthcare systems. Nowadays, most of the patients' diseases are analysed based on scanned medical images (MIs) as it is easy to analyse with pictorial information. In the scanning of MIs, segmentation plays an important role as this process helps to separate the region of interest area under analysis from that of region of non-interest area. Although many segmentation techniques have been introduced for MIs, no complete segmentation technique or algorithm is developed for all kinds of MIs, as segmentation technique suitable for one kind of MI may not be suitable for another MI. Hence, still there exists a scope for research in segmentation area under MIs. In this chapter, a segmentation technique based on dual-tree complex wavelet transform (DTCWT) based on morphological watershed algorithm is proposed to simplify the image for the better analysis of the infected area. The segmentation is implemented based on fusion technique and is evaluated using various quality metrics.
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