Brain Tumor Detection Based on Bilateral Symmetry Information
This addresses the problem of brain tumor detection for medical imaging applications, but it appears incremental as it builds on existing segmentation methods by incorporating symmetry information.
The paper tackled brain tumor detection in MRI images by proposing a segmentation algorithm based on bilateral symmetry information, resulting in an automated method for identifying tumor position and boundary that is described as flexible and convenient in experiments on real pictures.
Advances in computing technology have allowed researchers across many fields of endeavor to collect and maintain vast amounts of observational statistical data such as clinical data,biological patient data,data regarding access of web sites,financial data,and the like.Brain Magnetic Resonance Imaging(MRI)segmentation is a complex problem in the field of medical imaging despite various presented methods.MR image of human brain can be divided into several sub regions especially soft tissues such as gray matter,white matter and cerebrospinal fluid.Although edge information is the main clue in image segmentation,it can not get a better result in analysis the content of images without combining other information.The segmentation of brain tissue in the magnetic resonance imaging(MRI)is very important for detecting the existence and outlines of tumors.In this paper,an algorithm about segmentation based on the symmetry character of brain MRI image is presented.Our goal is to detect the position and boundary of tumors automatically.Experiments were conducted on real pictures,and the results show that the algorithm is flexible and convenient.