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- Vol. 1 Issue 3
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Enactment Valuation of Carcinoma with Segmentation Methods by Statistical Analysis
Authors
1M.Tech Scholar, ECE Department, IMS Engg College, UP, India. 2Assistant Professor, ECE Department, IMS EnggCollege, UP, India.
Article Information
- DOI
- No DOI
- Published In
- Volume 1, Issue 3 (2020)
- Published Online
- May-June 2020
- Pages
- 12-13
- Article Type
- Research Article
- Check for updates
- No DOI available for cross-reference
References
[1] A. Jemal, R. Siegel, E.Ward, Y. Hao, J. Xu, and M. J. Thun,“Cancer statistics, 2009,” CA: Cancer Journal for Clinicians,vol. 59, no. 4, pp. 225–249,2009.
[2] Welch, H. G., Prorok, P. C., O’Malley, A. J., & Kramer, B. S. (2016). Breast-cancer tumor size, overdiagnosis, and mammography screening effectiveness. New England Journal of Medicine, 375(15), 1438-1447.
[3] Litjens, G., Sánchez, C. I., Timofeeva, N., Hermsen, M., Nagtegaal, I., Kovacs, I., ...& Van Der Laak, J. (2016). Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis. Scientific reports,6, 26286.
[4] Kumar R., Srivastava R., Srivastava S. “Detection and Classification of Cancer from Microscopic Biopsy Images Using Clinically Significant and Biologically Interpretable Features” Proc of Journal of Medical Engineering, Volume 2015 (2015), Article ID 457906, 14pages.
[5] Srivaramangai, R., Hiremath, P., &Patil, A. S. (2017). Preprocessing mri images of colorectal cancer. International Journal of Computer Science Issues (IJCSI),14(1), 48.
[2] Welch, H. G., Prorok, P. C., O’Malley, A. J., & Kramer, B. S. (2016). Breast-cancer tumor size, overdiagnosis, and mammography screening effectiveness. New England Journal of Medicine, 375(15), 1438-1447.
[3] Litjens, G., Sánchez, C. I., Timofeeva, N., Hermsen, M., Nagtegaal, I., Kovacs, I., ...& Van Der Laak, J. (2016). Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis. Scientific reports,6, 26286.
[4] Kumar R., Srivastava R., Srivastava S. “Detection and Classification of Cancer from Microscopic Biopsy Images Using Clinically Significant and Biologically Interpretable Features” Proc of Journal of Medical Engineering, Volume 2015 (2015), Article ID 457906, 14pages.
[5] Srivaramangai, R., Hiremath, P., &Patil, A. S. (2017). Preprocessing mri images of colorectal cancer. International Journal of Computer Science Issues (IJCSI),14(1), 48.
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