1 OBJECTIVE AND PROBLEM STATEMENT
1.1 Objective
To implement Brain Tumour Segmentation based on Local Independent Projection-based Classification. In which Local independent projection based classification consider data distribution of different classes by learning Softmax regression model which improve classification performance.
1.2 Problem Statement
Brain tumour segmentation is an important procedure for early tumour diagnosis and radiotherapy planning. Although numerous brain tumour segmentation methods have been presented, enhancing tumour segmentation method is still challenging because brain tumour MRI images having complex characteristics, such as ambiguous tumour boundaries and high diversity in tumour appearance. To address this problem, I am going to implement Brain Tumour Segmentation based on Local Independent Projection-based Classification. This…show more content… During MR imaging, the patient is placed in a strong magnetic field which causes the protons in the water molecule of the body to align in either a parallel (low energy) or anti-parallel (high energy) orientation with the magnetic field. Then a radiofrequency pulse is introduced which forces the spinning protons to move out of equilibrium state. When a radio frequency pulse is stopped, the protons return to equilibrium state and produce a sinusoidal signal at a frequency dependent on the local magnetic field. Finally, a radio frequency coils or resonators within the scanner detects the signal and creates the image. Magnetic-resonance imaging is an imaging technique used primarily in medical settings to produce high quality images of the inside of the human body. A MRI is similar to CT, but it does not use X-rays. Instead, a strong, magnetic field is used to affect the orientation of protons, which behave like miniature magnets and tend to align themselves with the external