TECPRO

Medical image segmentation is an essential step for most subsequent image analysis tasks. The segmentation of anatomic structure in the brain plays a crucial role in Nero imaging analysis. Successful numerical algorithms can help researchers, physicians and neurosurgeons to investigate and diagnose the structure and function of the brain in both health and disease. This has motivated the need for segmentation techniques that are robust in application involving a broad range of anatomic structure, disease and image type. A new deformable model, the charged fluid model (CFM) is developed which uses the simulation of a charged fluid to segment anatomic structures in images of the brain. Conceptually, the charged fluid behaves like a liquid such that it flows through and around different obstacles.

The simulation evolves in two steps governed by Poisson’s equation. The first stem distributes the elements of the charged fluid within the propagation interface until an electrostatic equilibrium is achieved. The second step advances the propagating front of the charged fluid such that it deforms in to a new shape in response image gradient.

This approach requires no prior knowledge of anatomic structures, required the use only one parameter and providing sub-pixel precision in the region of interest. When compared to any other segmentation methods, very useful in segmenting regions with blurred boundaries and large variations in intensity of difficult objects in a variety of brain images and computation time takes to segmentation within few milliseconds this is impossible other methods means. Our organization is backed by qualified and experienced Neurologists and other doctors who assist student in preparing MRI brain segmentation projects.

D.Anandhi