Detection and 3D Modeling of Brain Tumor using Machine learning and Conformal Geometric Algebra
Soumya S Pillai, Rajesh Kannan Megalingam · 2020
Medical imaging or processing involves a wide range of computations on which the accuracy of analysis depends on the most. So to enhance the accuracy of analysis we need to reduce the computational geometric problems. Usually problems occur during the image segmentation or shape approximation or 3D modeling, and volumetric data registration. Con-formal geometric algebra is an effective paradigm to all this problems. The images we obtain after the MRI scan is 2D image from which the tumor has to be identified. This paper provides a key to identify the growth of the tumor in the regions inside the brain and to develop a 3D modeling of the tumor for the future reference which may help the doctor in the treatment of the tumor affected patient effectively. For the accurate prediction of whether a tumor is there in the brain related regions or not 2D image obtained must be first taken for the noise removal.