Knowledge Based Brain Tumor Segmentation Graphical User Interface
Kotikalapudi Raviteja1, Arun K Gupta2, Maya D Bhat3, Chandrajit Prasad4
1Kotikalapudi Raviteja, Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India.
2Dr. Arun K Gupta, Professor and Head, Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India.
3Dr. Maya D Bhat, Assistant Professor, Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India.
4Dr. Chandrajit Prasad, Assistant Professor, Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India.
Manuscript received on November 27, 2013. | Revised Manuscript received on December 13, 2013. | Manuscript published on December 30, 2013. | PP: 361-366 | Volume-3, Issue-2, December 2013. | Retrieval Number: B2489123213/2013©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper describes a knowledge based brain tumor segmentation system (KBBTS) using histogram interpretations for predicting brain tumor area from trans-axial Magnetic Resonance Imaging (MRI). A graphical user interface (GUI) was developed for the segmentation of brain tumor images. This system showed significant improvements over traditional threshold-based tumor segmentation methods. Although KBBTS is not designed to work in real time, it serves as potential research advancement for real time brain tumor segmentation using computer-aided systems with high performance.
Keywords: Glioma, graphical user interface (GUI), histogram, knowledge based brain tumor segmentation (KBBTS), trans-axial magnetic resonance imaging (MRI).