There has been a lot of work in segmentation of tumors in organs like the brain. Segmentation of bone tumor with MRI is not widely studied. Manual segmentation can be costly and time consuming. We study three automatic 3D segmentation techniques: Energy-based graph cuts, deep feed forward neural networks and mean shift clustering. Results show that, these methods can perform good quality segmentation (dice coefficient >70%) even with no human intervention. Tumor ADC values computed using these methods are comparable with those obtained from manual segmentation, showing that these methods can be used as a screening tool.