@article{MAKHILLJEAS2017122014931,
    title = {Performance Analysis of Total Variant Techniques for
Efficient Segmentation of Medical Images},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {12},
    number = {20},
    pages = {5343-5346},
    year = {2017},
    issn = {1816-949x},
    doi = {jeasci.2017.5343.5346},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.5343.5346},
    author = {Ramesh Babu and},
    keywords = {Brain tumour,TV,EADTV,MTV,performance,modified},
    abstract = {Denoising medical images is often required for efficient diagnosis of the diseases. Total Variance (TV)
is employed as a model of partial differential equation to identify the isolated noisy regions in the image. In the
due course, the TV has been modified to various versions. In this study, a performance analysis of adaptive
TV, median filtering and modified TV is performed, brain MRI of a patient subjected to tumour is considered
for denoising process. Later the same is segmented to have a clear vision of the tumour portion. The simulation
is carried out in MATLAB using image processing tool box. The evaluation is carried out using performance
metrics like PSNR.}
    }