Segmentation of Brain Tumour using Deep Neural Network |
Author(s): |
| J. Priyadarshini , PRINCE SHRI VENKATESHWARA PADMAVATHY ENGINEERING COLLEGE; P. Sneka, PRINCE SHRI VENKATESHWARA PADMAVATHY ENGINEERING COLLEGE; G. Vijayalakshmi, PRINCE SHRI VENKATESHWARA PADMAVATHY ENGINEERING COLLEGE; M. Pooja Nagpal, PRINCE SHRI VENKATESHWARA PADMAVATHY ENGINEERING COLLEGE |
Keywords: |
| DNNs, Brain Tumour, MRI |
Abstract |
|
BRAIN MR Image segmentation is a very important and challenging task that is needed for the purpose of diagnosing brain tumors and other neurological diseases. Brain tumors have different characteristics such as size, shape, location and image intensities. They may deform neighboring structures and if there is edema with the tumor, intensity properties of the nearby region change. Deep Neural Networks (DNNs) have recently attracted more attention due to their state-of-the-art performance on several datasets. DNNs have also been applied successfully to segmentation problems using DNNs in order to find the brain tumor. Deep Neural Networks (DNNs) are often successful in problems needing to extract information from complex, high-dimensional inputs, for which useful features are not obvious to design. To apply DNNs to brain tumor segmentation for the BRATS challenge. |
Other Details |
|
Paper ID: IJSRDV5I51335 Published in: Volume : 5, Issue : 5 Publication Date: 01/08/2017 Page(s): 1613-1617 |
Article Preview |
|
|
|
|
