title: Computer assisted diagnostic system in tumor radiography.
abstract: An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46%, which is a significant improvement than that of the existing results.
authors.affiliation: Department of Computer System & Technology, Faculty of Computer Science & Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia, ahmadprof05@siswa.um.edu.my.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Faisal
authors.forename: Sharmin
authors.initials: S
authors.lastname: Parveen
authors.forename: Shahriar
authors.initials: S
authors.lastname: Badsha
authors.forename: Hasan
authors.initials: H
authors.lastname: Sarwar
authors.forename: Ahmed Wasif
authors.initials: AW
authors.lastname: Reza
mesh_terms: D000465:Algorithms; D003199:Computer Systems; D006801:Humans; D008279:Magnetic Resonance Imaging; D009369:Neoplasms; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D059629:Signal-To-Noise Ratio