Corpus ID: 31893444

Lung Cancer Segmentation and Prediction Techniques Review

@inproceedings{Kumari2015LungCS,
  title={Lung Cancer Segmentation and Prediction Techniques Review},
  author={K. Kumari and P. Sharma},
  year={2015}
}
  • K. Kumari, P. Sharma
  • Published 2015
  • Lung cancer is a disease characterized by uncontrolled growth of cell in tissues of the lung. If left untreated, this growth can spread beyond the lungs, even, into other parts of the body [18]. Surgery, radiation therapy, and chemotherapy are used in the cure of lung carcinoma. In spite of that, the five-year survival rate for all stages combined is only 14% [19].The paper aims to study existing methods to detect the malignant nodules at earliest as well as suggest improvements so as to take… CONTINUE READING

    References

    SHOWING 1-10 OF 17 REFERENCES
    An automatic lung cancer detection from X-ray images obtained through yearly serial mass survey
    • 19
    Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images
    • 316
    • PDF
    Computer aided diagnosis system for lung cancer based on helical CT images
    • 50
    Lung cancer classification using neural networks for CT images
    • 201
    • PDF
    3-D Segmentation Algorithm of Small Lung Nodules in Spiral CT Images
    • 110
    • PDF
    Two-dimensional multi-criterion segmentation of pulmonary nodules on helical CT images.
    • 99
    Combination of computer-aided detection algorithms for automatic lung nodule identification
    • 57
    A Novel Automatic Extraction Method of Lung Texture Tree from HRCT Images
    • 9