TY  - BOOK
AU  - Aamir Hussain 
TI  - Automated Segmentation and Size Estimation of Brain Tumor from Mri Images
PY  - 2020///
CY  - Nawabshah
PB  - QUEST
KW  - Master of Engineering
KW  - Industrial Automation & Control
KW  - Department of Electronic Engineering
N1  - 






ABSTRACT


The segmentation of brain tum or using Magnetic Resonance Image (MRI) plays an important role m the medical  image process. The mam reason behind this process is to
 
separate the different types
 
0f t'
issues such as necrotic core, active cells and edema
 
from normal brain tissue of	h ·t
w  1 e matter (WM), gray matter (GM) and cerebrospinal
fluid   (CSF).   Presently   the	b	f	.	.	.	.
num  er  o	patients  of  brain tumor  are  increasing
significantly and the treatment of brain tumor is highly expensive. The rad10log1st an
neurologist have to do a tough job for the detection and treatment of brain tumor in the patients. Ultimately they need fast and efficient treatment methods. A  number of techniques to detect the brain tumor have been proposed in literature  each having merits and demerits. In this study a new automated system is proposed for brain tumor detection in which features of MRI images are extracted by using segmentation and morphological operation. The proposed framework consists of three phases; in the first phase the input MRI image is preprocessed to remove the noise and sharpen the image for the purpose of better segmentation of the tumor. In the second phase, the threshold segmentation is applied to extract the tumor region and quantify the tumor  area  in terms of square per inch and the number of pixels reserved by the tumor regions present in the brain. Finally, in the third phase the post-processing is done to remove the false regions so that the extracted tumor is better understandable to the radiologist. It was revealed that the proposed technique  offers tumor region  by consuming  less time  in milliseconds and low computational cost and classifies the tumor region in  the forefront  for the considerable  visual  investigation  that has a percentage  difference of
le	than 1%.

 
Keywords:	Magnetic Resonance operation.
 
Image
 
(MRI)•
 
Segmentation,	Morphological

UR  - http://tinyurl.com/2s437hzj
ER  -