Segmentation of Brain Tumor Based on MRI

By Dr. D Kishore Babu

Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. Here, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 3*3 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against over fitting, given the fewer number of weights in the network.

• Format: Paperback
• Language: English
• ISBN: 620255746X
• ISBN13: 9786202557467
• Release Date: June 2020
• Publisher: LAP Lambert Academic Publishing
• Length: 64 Pages
• Weight: 0.23 lbs.
• Dimensions: 0.1" x 6.0" x 9.0"