A Segmentation Approach Using Level Set Coding for Region Detection in MRI Images
Computer-aided diagnosis (CAD) systems for identifying brain tumor region in medical study have been investigated by various methods. This paper introduces an approach in computer-aided diagnosis for identification of brain tumor in early stages using level set segmentation method. The skull stripping and histogram equalization techniques are used as the processing techniques for the acquired image. The preprocessed image is used to segment region of interest using level set approach. The segmented image is fine-tuned by applying morphological operators. The proposed method gives better Mean Opinion Score (MOS) as compared to conventional level set method.
KeywordsImage segmentation MRI sample Level set (LS) coding Mean Opinion Score (MOS)
- 1.Cline HE, Lorensen E, Kikinis R, Jolesz F (1990) Three-dimensional segmentation of MR images of the head using probability and connectivity. J Comput Assist Tomogr 14:1037–1045Google Scholar
- 7.Warfield SK, Kaus MR, Jolesz FA, Kikinis R (1998) Adaptive template moderated spatially varying statistical segmentation. In: Wells WH, Colchester A, Delp S (eds) Proceedings of the first international conference on medical image computing and computer-assisted intervention. Springer, Boston, MA, 431–438Google Scholar
- 9.Zhu H, Francis HY, Lam FK, Poon PWF (1995) Deformable region model for locating the boundary of brain tumors. In: Proceedings of the IEEE 17th annual conference on engineering in medicine and biology, vol 411. IEEE, Montreal, QuebecGoogle Scholar
- 11.Sethian JA (1999) Level set methods and fast marching methods: evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science. Cambridge University PressGoogle Scholar