A Survey of MRI Segmentation Techniques for Brain Tumor Studies
Journal Title: Bonfring International Journal of Advances in Image Processing - Year 2016, Vol 6, Issue 3
Abstract
Brain tumor is one of the advancing brain illness among the existing population. The causes of the condition being non-deterministic, it is found that the survival rates of people suffering from brain tumor is very less. This medical condition lacks effective treatment and thus approaches that enable efficient treatment planning of the brain tumor is very crucial in the current context. Magnetic resonance image (MRI) scans are widely used in the diagnosis and subsequent treatment planning of the brain tumors. While in most of the cases only tumor regions are segregated from the MRI scans, segmentation of the tumor along with the healthy tissues of the brain such as white matter, gray matter and cerebrospinal fluid enable doctors to study the overall medical condition of the patient and treat him accordingly. The overall segmentation procedure includes noise removal, skull stripping, feature extraction and actual segmentation of various brain regions. Several methods used for each of these stages are discussed in this paper. The advantages and drawbacks of each of them are also highlighted.
Authors and Affiliations
Prajna Udupa, Sarvesh Vishwakarma
Buried Object Discrimination in a Ground Penetrating Radar Radargram
Ground Penetrating Radar (GPR) is a non-destructive technique used for the location of objects or interfaces buried beneath the earth's surface or located within a visually opaque structure. This research work proposes t...
Edge Detection Using Fuzzy Double Gradient Morphology
Detecting the edges of objects within images is a critical task for quality image processing. This paper proposes an edge detection operator based on the combination of fuzzy gradient morphology and Sobel operator. When...
Efficient Classification of Breast Lesion based on Deep Learning Technique
In this paper, a new method for Classification of Breast Cancer Images using deep Learning Algorithm are proposed. The Classification Algorithm appears as various features extracted from Healthy Breast images and U...
De-blurring Cardiac SPECT Images by Maximum Likelihood Approach
This paper presents a blind de-convolution algorithm for enhancing cardiac SPECT images by reducing the blur present in the image. The method is based on maximum likelihood estimate and in particular, the processin...
A Survey of MRI Segmentation Techniques for Brain Tumor Studies
Brain tumor is one of the advancing brain illness among the existing population. The causes of the condition being non-deterministic, it is found that the survival rates of people suffering from brain tumor is very less....