The main objective of this paper is to calculate volumes of brain tumors from sagittal, axial and coronal orientations. Brain tumor detection is a most important area in medical image processing. Brain cancer is a disease in which cells grow uncontrollably in the brain. It may affect any person at any stage. Brain tumor effects may not be the same for each person. Brain tumors can have a variety of shapes and sizes, it can appear at any location and in any different image intensities. Accurate measurements in brain diagnosis are quite difficult because of diverse shapes, sizes and appearances of tumors. The appearance of tumors on MR images varies greatly, due to tissue variation inside the tumor area and the diffuse growth of the tumor. Hence a variety of segmentation methods should be reviewed and a suitable method should be chosen to distinguish the tumor tissue from the surrounding brain to gain exact volume values. This includes implementation of a spectral clustering segmentation method and 2-dimensional (2D) visualization can be done to each MRI slices. For calculating the tumor volume its important to get the tumor area. Normally its very difficult to calculate the tumor area from a irregular tumor shape. To overcome this problem detect the convex hull region from segmentation result and calculate the convex area from convex hull image. At last frustum model method is used for calculating the tumor volume.