  Image segmentation is often performed on medical images for identifying
diseases in clinical evaluation. Hence it has become one of the major research
areas. Conventional image segmentation techniques are unable to provide
satisfactory segmentation results for medical images as they contain
irregularities. They need to be pre-processed before segmentation. In order to
obtain the most suitable method for medical image segmentation, we propose a
two stage algorithm. The first stage automatically generates a binary marker
image of the region of interest using mathematical morphology. This marker
serves as the mask image for the second stage which uses GrabCut on the input
image thus resulting in an efficient segmented result. The obtained result can
be further refined by user interaction which can be done using the Graphical
User Interface (GUI). Experimental results show that the proposed method is
accurate and provides satisfactory segmentation results with minimum user
interaction on medical as well as natural images.
