Brain Tumor Segmentation from Multimodal MR Images Using Rough Sets

Author(s):  
Rupsa Saha ◽  
Ashish Phophalia ◽  
Suman K. Mitra
Author(s):  
Palash Ghosal ◽  
Shanmukha Reddy ◽  
Charan Sai ◽  
Vikas Pandey ◽  
Jayasree Chakraborty ◽  
...  

Brain tumors are the result of unusual growth and unrestrained cell disunity in the brain. Most of the medical image application lack in segmentation and labeling. Brain tumors can lead to loss of lives if they are not detected early and correctly. Recently, deep learning has been an important role in the field of digital health. One of its action is the reduction of manual decision in the diagnosis of diseases specifically brain tumor diagnosis needs high accuracy, where minute errors in judgment may lead to loss therefore, brain tumor segmentation is an necessary challenge in medical side. In recent time numerous ,methods exist for tumor segmentation with lack of accuracy. Deep learning is used to achieve the goal of brain tumor segmentation. In this work, three network of brain MR images segmentation is employed .A single network is compared to achieve segmentation of MR images using separate network .In this paper segmentation has improved and result is obtained with high accuracy and efficiency.


2018 ◽  
Vol 9 (1) ◽  
pp. 1844-1848 ◽  
Author(s):  
Fazel Mirzaei ◽  
Mohammad Reza Parishan ◽  
Mohammadjavad Faridafshin ◽  
Reza Faghihi ◽  
Sedigheh Sina

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 25335-25349 ◽  
Author(s):  
Tamjid Imtiaz ◽  
Shahriar Rifat ◽  
Shaikh Anowarul Fattah ◽  
Khan A. Wahid

Sign in / Sign up

Export Citation Format

Share Document