Abstract
In lung cancer diagnosis, growth of pulmonary nodule should be detected perfectly. Mostly watershed segmentation methods play a very important role in lung CT images to detect their growth. But this method detection will be ineffective in terms of energy function and speed as well. The proposed modified graph-cut technique is providing the good performing result in the speed and accuracy of the process than the conservative graph cut methods. Also, this research paper is proposed adaptive shape based interactive approach to segmentation for lung CT scan image and provide a more efficient. This proposed algorithm is proving that the energy function of the system is lesser than old methods. In this research paper, applying shape-based technique in segmentation technique has been proposed and proved for better accuracy with low energy function.
Publisher
Inventive Research Organization
Reference14 articles.
1. [1] Ahmed Soliman et al“Accurate Lungs Segmentation on CT Chest Images by Adaptive Appearance-Guided Shape Modeling” Published in IEEE Transactions on Medical Imaging PP(99):1-1 September 2016 DOI: 10.1109/TMI.2016.2606370.
2. [2] Furqan Shaukat et al “An Efficient Algorithmic Solution for automatic Segmentation of Lungs from CT images” Published in Pakistan journal of science 70(1):71-8 March 2018
3. [3] D. L. Pham, C. Y. Xu, and J. L Prince, "Current Methods in Medical Image Segmentation," in Annual Review of Biomedical Engineering, Vol. 2, Pages: 1-5, 2000.
4. [4] I. Sluimer, P. Waes, M. Viergever, and B. Ginneken, “Computer-aided diagnosis in high resolution CT of the lungs,” Med. Phys. 30, 3081–3090. 2003.
5. [5] J. Keller, F. Edwards, and R. Rundle, “Automatic outlining of regions on CT scans,” J. Comput. Assist. Tomogr. 5, 240– 245 .1981.
Cited by
16 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献