A Deep Belief Network Based Brain Tumor Detection in MRI Images
Abstract: Glioma is a common and malignant tumor, which may lead to short life span in their highest grade. Thus to improve the quality of life of cancer patients is the early diagnosis of brain tumor, which is a stage of treatment. MRI (Magnetic Resonance Imaging) is widely used medical imaging technique used to assess tumors, but large amount of data produced by MRI may vary greatly. Thus manual detection will be a challenge. To detect brain tumor in magnetic resonance imaging many automated diagnostic systems play an important role. The system may mainly include three steps namely preprocessing, classification and post processing. A DBN (Deep Belief Network) based classification method is used to identify brain tumor in MRI images which can yield the result more accurately.
Keywords: Glioma, Oncological, Magnetic Resonance Imaging, Deep Belief Network
How to Cite?: Thahseen P, Anish Kumar B, "A Deep Belief Network Based Brain Tumor Detection in MRI Images", Volume 6 Issue 7, July 2017, International Journal of Science and Research (IJSR), Pages: 495-500, https://www.ijsr.net/getabstract.php?paperid=ART20175321, DOI: https://dx.doi.org/10.21275/ART20175321