“EXTRACTION AND QUANTIFICATION OF BRAIN TUMOR FROM MRI IMAGE”
“EXTRACTION AND QUANTIFICATION OF BRAIN TUMOR FROM MRI IMAGE”
CHAPTER 1
INTRODUCTION
1.1 GENERAL: The principle task of our project is to recognize a tumor and its quantifications from a particular MRI scan of a brain image using digital image processing techniques and compute the area of the tumor by fully automated process. In medical imaging, segmentation of images plays a vital role in stages which occur before implementing object recognition. The critical problem is finding the tumor location automatically and later finding its boundary precisely. An important factor in detecting tumor from healthy tissues is the difference in intensity level. However, relying only on the intensity level is usually not enough. The spatial information available in clusters of pixels that form a tumor should also be used in the detection process. Accurate measurements in brain diagnosis are quite difficult because of diverse shapes, sizes and appearances of tumors. Tumors can grow abruptly causing defects in neighbouring tissues also, which gives an overall abnormal structure for healthy tissues as well.
In this paper, we will develop a technique of SEGMENTATION of a brain tumor by using segmentation in conjunction with morphological operations. In our projects the MRI image of brain tumor is given as input to MATLAB (image processing toolbox) coding. It will extract the tumor portion and calculate its area within a small duration automatically. Here the quality of the detection is improved.
1.2 IMAGE : Images may be two-dimensional, such as a photograph, screen display, and as well as a three-dimensional, such as a statue or hologram. They may be captured by optical devices-such as cameras, mirrors, lenses, telescopes, microscopes etc and natural objects and phenomena, such as the human eye or water surfaces. The word image is also used in the broader sense of any two-dimensional
CHAPTER 1
INTRODUCTION
1.1 GENERAL: The principle task of our project is to recognize a tumor and its quantifications from a particular MRI scan of a brain image using digital image processing techniques and compute the area of the tumor by fully automated process. In medical imaging, segmentation of images plays a vital role in stages which occur before implementing object recognition. The critical problem is finding the tumor location automatically and later finding its boundary precisely. An important factor in detecting tumor from healthy tissues is the difference in intensity level. However, relying only on the intensity level is usually not enough. The spatial information available in clusters of pixels that form a tumor should also be used in the detection process. Accurate measurements in brain diagnosis are quite difficult because of diverse shapes, sizes and appearances of tumors. Tumors can grow abruptly causing defects in neighbouring tissues also, which gives an overall abnormal structure for healthy tissues as well.
In this paper, we will develop a technique of SEGMENTATION of a brain tumor by using segmentation in conjunction with morphological operations. In our projects the MRI image of brain tumor is given as input to MATLAB (image processing toolbox) coding. It will extract the tumor portion and calculate its area within a small duration automatically. Here the quality of the detection is improved.
1.2 IMAGE : Images may be two-dimensional, such as a photograph, screen display, and as well as a three-dimensional, such as a statue or hologram. They may be captured by optical devices-such as cameras, mirrors, lenses, telescopes, microscopes etc and natural objects and phenomena, such as the human eye or water surfaces. The word image is also used in the broader sense of any two-dimensional
References: [8] P.Vasuda, S.Satheesh, ‖Improved Fuzzy C-Means Algorithm for MR Brain Image Segmentation, Page(s): 1713-1715, (IJCSE) International Journal on Computer Science and Engineering,Vol. 02, 05, 2010.