Also it is used in the better understanding of the metabolite type produced in infarctions, ischemia, and tumors. The potential clinical applications today are the differentiation of cancerous from non-cancerous tissue, infarcted from the normal tissue and necrosis from recurrent tumor. Segmentation is the process of assigning labels to pixels in 2D images or voxels in 3D images. The effect is that the image is split up into segments also called as regions or areas. The segmentation techniques can be classified into manual, semiautomatic and automatic techniques.
Manual technique is too tedious to be used in clinical trials.
Automatic segmentation techniques suffer from the inaccuracies created by the inpriori knowlegde fed into the technique. Semiautomatic segmentation is the best of all because of its ease, fastness and manual intervention. For clinical purposes segmentation techniques using MRI has been widely used in phase three trials in multiple sclerosis, and in monitoring brain infarctions, brain tumors, dementia and brain atrophy. Reliable 3D images constructed from the segmented images helps understand the relation between the lesions and surrounding normal brain structures. Three dimensional imaging is now widely available and used often to aid in the comprehension and application of volumetric data to diagnosis, planning and therapy.