Brain Tumor Detection based on Multi-parameter MRI Image Analysis
Rajeev Ratan A, Sanjay Sharma B, S. K. SharmaC
A Lecturer, Department of E & IE, Apeejay College of Engineering, Sohna, Gurgaon, Haryana, India
B Assistant Professor, Department of ECE, Thapar University, Patiala, Punjab.
C Professor, Department of ECE, Apeejay College of Engineering, Sohna, Gurgaon, Haryana, India.
Abstract
Segmentation of anatomical regions of the brain is the fundamental problem in medical image analysis. While surveying the literature, it has been found out that no work has been done in segmentation of brain tumor by using watershed in MATLAB Environment. In this paper, a brain tumor segmentation method has been developed and validated segmentation on 2D & 3D MRI Data. This method can segment a tumor provided that the desired parameters are set properly. This method does not require any initialization while the others require an initialization inside the tumor. The visualization and quantitative evaluations of the segmentation results demonstrate the effectiveness of this approach. In this study, after a manual segmentation procedure the tumor identification, the investigations has been made for the potential use of MRI data for improving brain tumor shape approximation and 2D & 3D visualization for surgical planning and assessing tumor. Surgical planning now uses both 2D & 3D models that integrate data from multiple imaging modalities, each highlighting one or more aspects of morphology or functions. Firstly, the work was carried over to calculate the area of the tumor of single slice of MRI data set and then it was extended to calculate the volume of the tumor from multiple image MRI data set.
Keywords: Brain tumor, Magnetic resonance Imaging (MRI), Image segmentation, watershed segmentation, MATLAB.
( P1150906627,
1 MB)
BibTex:
@ARTICLE{P1150906627,
AUTHOR = {Rajeev Ratan and
Sanjay Sharma and S. K. Sharma},
TITLE = {Brain Tumor
Detection based on Multi-parameter MRI Image
Analysis },
JOURNAL ={ICGST
International Journal on Graphics, Vision
and Image Processing, GVIP},
YEAR = {2009},
VOLUME = {09},
ISSUE ={III},
PAGES={9--17} }
(P1150906627,
1 MB)
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