An Effective Automatic Detection of Lung Tumor Based on Novel Optimized Chan-Vese Algorithm

  • Authors

    • Lim J Seelan Research scholar, Department of EEE, Noorul Islam University, Thucklay, Tamilnadu, India
    • Dr. L. Padma Suresh Baselios Mathew II College of Engineering, Sasthamkotta, Kerala-690521
    https://doi.org/10.14419/ijet.v7i4.39.26266

    Received date: January 20, 2019

    Accepted date: January 20, 2019

    Published date: December 13, 2018

  • Histogram equalization, Curvelet transform, adaptive concave hull, optimized chan-vese

  • Abstract

    One of the severe health hazards is lung cancer. United States alone bears approximately 25% lung cancer burden. This type of cancer is cured if it is detected in an earlier stage and reduces mortality rate. With the rapid rising of lung cancer patients, the CAD (Computer Aided Detection) method plays a significant role in the field of automatic recognition for medical images. This method focused on automatic identification of lung nodule using optimized chan-vese algorithms. The computer automatic system consist of following steps: - image acquisition, image preprocessing, and image segmentation. This method is mainly helpful for automated finding of lung nodules that are appended to the chest wall. The final output shows the application of the proposed method in the medical field will bring great progress for medical development.

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  • How to Cite

    Seelan, L. J. ., & Suresh, D. L. P. . (2018). An Effective Automatic Detection of Lung Tumor Based on Novel Optimized Chan-Vese Algorithm. International Journal of Engineering and Technology, 7(4.39), 737-741. https://doi.org/10.14419/ijet.v7i4.39.26266