@article{MAKHILLAJIT201615196409,
    title = {Investigation of Optimal Segmentation Algorithm for CT Lung
Nodules Using Cad System},
    journal = {Asian Journal of Information Technology},
    volume = {15},
    number = {19},
    pages = {3742-3747},
    year = {2016},
    issn = {1682-3915},
    doi = {ajit.2016.3742.3747},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2016.3742.3747},
    author = {K.,S.,C. Nelson Kennedy and},
    keywords = {Segmentation,computer aided diagnosis,region growing,earth movers distance,firefly search,fuzzy c-means},
    abstract = {Computer Aided Diagnosis (CAD) has been playing a significant role in cancer detection for the past two decades. This research study mainly focuses on developing a CAD system for early detection of lung cancer with improved accuracy. The proposed system helps to reduce unnecessary biopsy and surgery. In this research, three methodologies namely Automatic Region Growing (ARG), Histogram based Earth-Mover’s Distance (HEMD), Firefly Search Fuzzy C-Means (FSFC) algorithm have been developed for improving the accuracy of the computer aided diagnosis of lung cancer from CT images. The performance of three segmentation methodologies are evaluated and compared to prove that the proposed Firefly Search Fuzzy C-means methodology outperforms the existing algorithms.}
    }