@article{MAKHILLIJSSCEA201912328789,
    title = {A Hybrid Enhanced ICA Approach for Segmentation of Brain MR Image},
    journal = {International Journal of System Signal Control and Engineering Application},
    volume = {12},
    number = {3},
    pages = {48-58},
    year = {2019},
    issn = {1997-5422},
    doi = {ijssceapp.2019.48.58},
    url = {https://makhillpublications.co/view-article.php?issn=1997-5422&doi=ijssceapp.2019.48.58},
    author = {Shaik and},
    keywords = {Gaussian mixture mode,ICA,MRI,segmentation,manual analysis},
    abstract = {Medical imaging and analysis has become an
integrated tool for effective and efficient management of
any disease. The significance of medical imaging is
diagnosing. Diseased state of human brain is huge. One
such diagnosis is identification and extraction of brain
tumor. The utility of any image is influenced by the
quantity and quality of information that can be extracted
lent of it. The processing power of humans are
tremendous and they posses every complex interpreting
skill. Humans are capable of performing cognitive
analysis of an image. Some of the typical issues in regard
to visual interpretation and manual analysis include wide
difference in sense of perception between different users,
human fatigue and for most of the time human one
capable of providing a qualitative analysis rather than a
quantifying one. A computer based image analysis
accounts for most of these problems and can help in
saving crucial time needed to respond to a medical
emergency. Effective image processing methods can serve
as potent tools that can help in an affordable and effective
healthcare practices. This research work illustrates one
such tool that will significantly contribute towards the
analysis and the interpretation of MRI images for tumor
detection and classification. An enhanced and modified
Gaussian mixture mode model and the ICA segmentation
approach has been employed for segmenting brain tumors
in MR images.}
    }