Level set and applications using GPU programming

In recent years, with the development of graphics processors, graphics cards have been widely used to perform general-purpose calculations. Especially with release of CUDA C programming languages in 2007, most of the researchers have been used CUDA C programming language for the processes which needs high performance computing. In this thesis, a scaling approach for image segmentation using level sets is carried out by the GPU programming techniques. Approach to level sets is mainly based on the solution of partial differential equations. The proposed method does not require the solution of partial differential equation. Scaling approach, which uses basic geometric transformations, is used. Thus, the required computational cost reduces. The use of the CUDA programming on the GPU has taken advantage of classic programming as spending time and performance. Thereby results are obtained faster. The use of the GPU has provided to enable real-time processing. The developed application in this study is used to find tumor on MRI brain images.