Brain Tumor Detection Based On Symmetry Information
This work addresses brain tumor detection for medical applications, but it appears incremental as it adds a feature to existing segmentation systems.
The paper tackled the challenge of brain tumor segmentation in MRI images, where intensity alone is weakly correlated with anatomical meaning, by proposing an approach that uses bilateral symmetry information as an additional feature to improve segmentation.
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. This paper addresses some of the challenging issues on brain magnetic resonance (MR) image tumor segmentation caused by the weak correlation between magnetic resonance imaging (MRI) intensity and anatomical meaning. With the objective of utilizing more meaningful information to improve brain tumor segmentation, an approach which employs bilateral symmetry information as an additional feature for segmentation is proposed. This is motivated by potential performance improvement in the general automatic brain tumor segmentation systems which are important for many medical and scientific applications